Monitor and integrate funding rounds into company profiles
We need to analyze websites that announce funding rounds and integrate this data into our company profiles. This will allow us to track recent fundraises, provide real-time alerts, and enrich company financial data with structured funding information. 🔹 Why? • Enables real-time insights into newly funded companies. • Helps users track startup growth and investment trends. • Improves company profiling with detailed financial event tracking. 🔹 How it works? 1. Identify key funding data sources: • Websites like Crunchbase, PitchBook, CB Insights, TechCrunch, Dealroom, and AngelList. • Public announcements, press releases, and investment databases. 2. Develop an AI-powered data extraction pipeline: • Use web scraping and AI NLP models to analyze funding news. • Extract funding amount, investors, round type (Seed, Series A, B, etc.), and date. 3. Structure and store funding data in company profiles: • Add a funding_rounds field in the JSON profile: { "funding_rounds": [ { "amount": "25M", "currency": "USD", "round": "Series A", "investors": ["Sequoia Capital", "Accel"], "date": "2024-03-10" } ] } 4. Set up real-time alerts for new funding events: • Trigger notifications via webhooks, Slack, and email. • Allow users to subscribe to funding updates for specific industries or companies. 5. Enable search and filtering by funding status: • Add API endpoints to search for companies based on funding rounds. • Allow filtering by investment amount, round type, or date. 6. Ensure data accuracy and validation: • Cross-check funding details across multiple sources before confirming. • Maintain a confidence score for each funding event to track reliability. 7. Automate periodic updates: • Implement a continuous monitoring system to detect new funding events. • Use AI to validate and refine extracted data over time.
Julien Le Coupanec 7 days ago
Features
Monitor and integrate funding rounds into company profiles
We need to analyze websites that announce funding rounds and integrate this data into our company profiles. This will allow us to track recent fundraises, provide real-time alerts, and enrich company financial data with structured funding information. 🔹 Why? • Enables real-time insights into newly funded companies. • Helps users track startup growth and investment trends. • Improves company profiling with detailed financial event tracking. 🔹 How it works? 1. Identify key funding data sources: • Websites like Crunchbase, PitchBook, CB Insights, TechCrunch, Dealroom, and AngelList. • Public announcements, press releases, and investment databases. 2. Develop an AI-powered data extraction pipeline: • Use web scraping and AI NLP models to analyze funding news. • Extract funding amount, investors, round type (Seed, Series A, B, etc.), and date. 3. Structure and store funding data in company profiles: • Add a funding_rounds field in the JSON profile: { "funding_rounds": [ { "amount": "25M", "currency": "USD", "round": "Series A", "investors": ["Sequoia Capital", "Accel"], "date": "2024-03-10" } ] } 4. Set up real-time alerts for new funding events: • Trigger notifications via webhooks, Slack, and email. • Allow users to subscribe to funding updates for specific industries or companies. 5. Enable search and filtering by funding status: • Add API endpoints to search for companies based on funding rounds. • Allow filtering by investment amount, round type, or date. 6. Ensure data accuracy and validation: • Cross-check funding details across multiple sources before confirming. • Maintain a confidence score for each funding event to track reliability. 7. Automate periodic updates: • Implement a continuous monitoring system to detect new funding events. • Use AI to validate and refine extracted data over time.
Julien Le Coupanec 7 days ago
Features
Analyze SSL certificates to cluster domains & identify company operations
We need to analyze SSL certificates to cluster domain names together, associating them with the same company when possible. By leveraging SSL certificate metadata, we can also infer where a company operates based on domain extensions (TLDs) and certificate issuers. 🔹 Why? • Helps identify related domains belonging to the same organization. • Improves company clustering and entity resolution. • Provides insights into a company’s geographic operations based on TLDs & SSL metadata. 🔹 How it works? 1. Extract SSL certificate metadata: • Retrieve certificate issuer, subject, SAN (Subject Alternative Names), expiration date, etc. • Identify shared certificates across multiple domains. 2. Cluster domain names based on SSL similarities: • Associate domains with the same certificate authority and issuer. • Group domains based on shared SANs (Subject Alternative Names). • Detect companies operating multiple domains under a single certificate. 3. Infer company locations from TLDs & certificates: • Analyze domain extensions (e.g., .fr, .de, .sg) to map regional operations. • Use SSL certificate country fields to validate location presence. 4. Store & expose the cluster data: • Save domain associations in the database. • Allow querying “show me all domains related to this company”. • Provide an API endpoint for SSL-based domain clustering. 5. Improve detection & prevent misclassification: • Handle multi-tenant CDNs & wildcard certificates carefully. • Exclude generic hosting services that don’t indicate ownership. 6. Enhance Power’s company mapping: • Add SSL-based company relationships to improve domain-to-company accuracy. • Use SSL insights to cross-check company operations & global reach. 7. Automate periodic SSL scans: • Set up scheduled crawls to update SSL certificate data regularly. • Ensure data freshness for accurate clustering.
Julien Le Coupanec 7 days ago
Datapoints
Analyze SSL certificates to cluster domains & identify company operations
We need to analyze SSL certificates to cluster domain names together, associating them with the same company when possible. By leveraging SSL certificate metadata, we can also infer where a company operates based on domain extensions (TLDs) and certificate issuers. 🔹 Why? • Helps identify related domains belonging to the same organization. • Improves company clustering and entity resolution. • Provides insights into a company’s geographic operations based on TLDs & SSL metadata. 🔹 How it works? 1. Extract SSL certificate metadata: • Retrieve certificate issuer, subject, SAN (Subject Alternative Names), expiration date, etc. • Identify shared certificates across multiple domains. 2. Cluster domain names based on SSL similarities: • Associate domains with the same certificate authority and issuer. • Group domains based on shared SANs (Subject Alternative Names). • Detect companies operating multiple domains under a single certificate. 3. Infer company locations from TLDs & certificates: • Analyze domain extensions (e.g., .fr, .de, .sg) to map regional operations. • Use SSL certificate country fields to validate location presence. 4. Store & expose the cluster data: • Save domain associations in the database. • Allow querying “show me all domains related to this company”. • Provide an API endpoint for SSL-based domain clustering. 5. Improve detection & prevent misclassification: • Handle multi-tenant CDNs & wildcard certificates carefully. • Exclude generic hosting services that don’t indicate ownership. 6. Enhance Power’s company mapping: • Add SSL-based company relationships to improve domain-to-company accuracy. • Use SSL insights to cross-check company operations & global reach. 7. Automate periodic SSL scans: • Set up scheduled crawls to update SSL certificate data regularly. • Ensure data freshness for accurate clustering.
Julien Le Coupanec 7 days ago
Datapoints
Add EuroNext, Next40, and Next120 company listings as a new datapoint
We need to integrate major European stock market indices, including EuroNext, Next40, and Next120, into our company profiles. This will allow users to identify publicly traded companies in these indices and enhance segmentation for financial and investment purposes. 🔹 Why? • Provides valuable financial insights for investors and analysts. • Enhances company categorization by stock market indices. • Allows users to filter and analyze companies based on their market presence. 🔹 How it works? 1. Determine the correct datapoint name: • Suggestion: stock_index_membership • Example format: { "stock_index_membership": ["Euronext", "Next40", "Next120"] } 2. Find reliable data sources: • Use official Euronext APIs, stock exchange websites, or financial databases. • Scrape or periodically update Next40 & Next120 listings from their respective sources. 3. Integrate data into company profiles: • Store index membership as an array for companies. • Ensure data updates dynamically as companies enter or exit these indices. 4. Allow API search & filtering: • Enable users to search for companies by index membership. • Add a filter in the UI to display relevant stock-listed companies. 5. Ensure periodic updates: • Implement an automatic update system to reflect quarterly changes. • Cross-check with official sources to maintain accuracy. 6. Test UI & API implementations: • Ensure companies display the correct stock index affiliations. • Validate data accuracy before deployment.
Julien Le Coupanec 7 days ago
Features
Add EuroNext, Next40, and Next120 company listings as a new datapoint
We need to integrate major European stock market indices, including EuroNext, Next40, and Next120, into our company profiles. This will allow users to identify publicly traded companies in these indices and enhance segmentation for financial and investment purposes. 🔹 Why? • Provides valuable financial insights for investors and analysts. • Enhances company categorization by stock market indices. • Allows users to filter and analyze companies based on their market presence. 🔹 How it works? 1. Determine the correct datapoint name: • Suggestion: stock_index_membership • Example format: { "stock_index_membership": ["Euronext", "Next40", "Next120"] } 2. Find reliable data sources: • Use official Euronext APIs, stock exchange websites, or financial databases. • Scrape or periodically update Next40 & Next120 listings from their respective sources. 3. Integrate data into company profiles: • Store index membership as an array for companies. • Ensure data updates dynamically as companies enter or exit these indices. 4. Allow API search & filtering: • Enable users to search for companies by index membership. • Add a filter in the UI to display relevant stock-listed companies. 5. Ensure periodic updates: • Implement an automatic update system to reflect quarterly changes. • Cross-check with official sources to maintain accuracy. 6. Test UI & API implementations: • Ensure companies display the correct stock index affiliations. • Validate data accuracy before deployment.
Julien Le Coupanec 7 days ago
Features
Implement a news aggregation feature for company profiles and API
We need to fetch and display the latest news articles related to a company, both in our API and in the company profile UI. This feature would be available as a premium datapoint based on subscription tiers and could also be integrated into our Chrome extension for quick access. 🔹 Why? • Provides real-time business intelligence by showing recent news. • Enhances company profiles with up-to-date insights. • Offers a valuable premium feature for paying users. 🔹 How it works? 1. Develop an API endpoint for company news: • Users can query recent news articles for a company. • Support filtering by date, source, and keyword relevance. • Make it a premium datapoint for paid subscribers. 2. Integrate the news feed in company profiles: • Display the latest articles related to a company inside the UI. • Ensure the news section is clean and well-structured. 3. Enhance the Chrome extension: • Allow users to see recent news articles when viewing a company’s profile in the extension. 4. Choose data sources: • Use Google News API, Bing News API, or other reliable sources. • Implement a scraper or RSS feed processor for niche sources if needed. 5. Optimize performance & relevance: • Ensure articles are filtered by company name/domain to avoid unrelated content. • Cache recent results to minimize API requests and improve speed. 6. Enable search & notifications: • Users can search for company-related news using our API. • Implement an alert system to notify users of breaking news. 7. Monitor & improve: • Regularly check for duplicate or irrelevant articles. • Improve ranking algorithms to prioritize the most relevant news.
Julien Le Coupanec 7 days ago
Datapoints
Implement a news aggregation feature for company profiles and API
We need to fetch and display the latest news articles related to a company, both in our API and in the company profile UI. This feature would be available as a premium datapoint based on subscription tiers and could also be integrated into our Chrome extension for quick access. 🔹 Why? • Provides real-time business intelligence by showing recent news. • Enhances company profiles with up-to-date insights. • Offers a valuable premium feature for paying users. 🔹 How it works? 1. Develop an API endpoint for company news: • Users can query recent news articles for a company. • Support filtering by date, source, and keyword relevance. • Make it a premium datapoint for paid subscribers. 2. Integrate the news feed in company profiles: • Display the latest articles related to a company inside the UI. • Ensure the news section is clean and well-structured. 3. Enhance the Chrome extension: • Allow users to see recent news articles when viewing a company’s profile in the extension. 4. Choose data sources: • Use Google News API, Bing News API, or other reliable sources. • Implement a scraper or RSS feed processor for niche sources if needed. 5. Optimize performance & relevance: • Ensure articles are filtered by company name/domain to avoid unrelated content. • Cache recent results to minimize API requests and improve speed. 6. Enable search & notifications: • Users can search for company-related news using our API. • Implement an alert system to notify users of breaking news. 7. Monitor & improve: • Regularly check for duplicate or irrelevant articles. • Improve ranking algorithms to prioritize the most relevant news.
Julien Le Coupanec 7 days ago
Datapoints
Calculate and integrate NAF codes for company classification
We need to identify and assign NAF (Nomenclature d’Activités Françaises) codes to companies and allow users to search for businesses based on their NAF code. This classification is widely used in France for categorizing economic activities and could enhance our company segmentation system. 🔹 Why? • Provides a structured classification for French businesses. • Allows searching and filtering companies by NAF codes. • Enhances business profiling by adding a new industry classification metric. • Can be automatically predicted for companies using our LLM model. 🔹 How it works? 1. Verify NAF code sources: • Check official INSEE databases (Institut National de la Statistique et des Études Économiques). • Use existing classification mappings from SIC, NAICS, or other taxonomies. 2. Develop a method to assign NAF codes: • If the company already has an official NAF code, retrieve it. • If missing, use our LLM to infer the NAF code based on company description, industry, and services. 3. Store NAF codes in the company profile: • Add a naf_code field in the company data object. • Ensure compatibility with other classification systems (NAICS, SIC, etc.). 4. Implement a search filter for NAF codes: • Allow users to search and filter companies by their NAF code. • Support cross-referencing between different industry classifications. 5. Update API endpoints: • Provide an endpoint to retrieve the NAF code of a company. • Allow bulk queries for industry classification lookups. 6. Ensure periodic updates: • Regularly validate and refresh NAF codes using external sources. • Improve LLM predictions based on real-world corrections and validations.
Julien Le Coupanec 7 days ago
Datapoints
Calculate and integrate NAF codes for company classification
We need to identify and assign NAF (Nomenclature d’Activités Françaises) codes to companies and allow users to search for businesses based on their NAF code. This classification is widely used in France for categorizing economic activities and could enhance our company segmentation system. 🔹 Why? • Provides a structured classification for French businesses. • Allows searching and filtering companies by NAF codes. • Enhances business profiling by adding a new industry classification metric. • Can be automatically predicted for companies using our LLM model. 🔹 How it works? 1. Verify NAF code sources: • Check official INSEE databases (Institut National de la Statistique et des Études Économiques). • Use existing classification mappings from SIC, NAICS, or other taxonomies. 2. Develop a method to assign NAF codes: • If the company already has an official NAF code, retrieve it. • If missing, use our LLM to infer the NAF code based on company description, industry, and services. 3. Store NAF codes in the company profile: • Add a naf_code field in the company data object. • Ensure compatibility with other classification systems (NAICS, SIC, etc.). 4. Implement a search filter for NAF codes: • Allow users to search and filter companies by their NAF code. • Support cross-referencing between different industry classifications. 5. Update API endpoints: • Provide an endpoint to retrieve the NAF code of a company. • Allow bulk queries for industry classification lookups. 6. Ensure periodic updates: • Regularly validate and refresh NAF codes using external sources. • Improve LLM predictions based on real-world corrections and validations.
Julien Le Coupanec 7 days ago
Datapoints
Retrieve company patents and add a premium API endpoint
We need to identify the patents owned by a company and integrate this data into our API. This will allow users to access a company’s intellectual property portfolio and gain insights into their innovations. This patents datapoint will be a premium feature, available only for users with the appropriate subscription plan. 🔹 Why? • Adds valuable intellectual property data to company profiles. • Helps users analyze a company’s innovation & technology focus. • Creates a premium datapoint for monetization. 🔹 How it works? 1. Find reliable data sources for patents: • Google Patents API • USPTO (United States Patent and Trademark Office) • WIPO (World Intellectual Property Organization) • EUIPO (European Union Intellectual Property Office) 2. Develop an API endpoint to retrieve patents: • Allow searches by company name, domain, or registration ID. • Fetch patent titles, descriptions, filing dates, inventors, and legal statuses. 3. Integrate patent data into company profiles: • Display the number of patents in the Profit Vision section. • Include a detailed list of patents for premium users. 4. Make patents a premium datapoint: • Restrict detailed patent information to paid subscribers. • Allow basic patent count visibility for all users. 5. Ensure scheduled updates: • Refresh patent records periodically to include newly filed patents. 6. Provide filtering & search capabilities: • Allow users to search companies based on patent ownership. • Enable filtering by patent category, technology, or region.
Julien Le Coupanec 7 days ago
Datapoints
Retrieve company patents and add a premium API endpoint
We need to identify the patents owned by a company and integrate this data into our API. This will allow users to access a company’s intellectual property portfolio and gain insights into their innovations. This patents datapoint will be a premium feature, available only for users with the appropriate subscription plan. 🔹 Why? • Adds valuable intellectual property data to company profiles. • Helps users analyze a company’s innovation & technology focus. • Creates a premium datapoint for monetization. 🔹 How it works? 1. Find reliable data sources for patents: • Google Patents API • USPTO (United States Patent and Trademark Office) • WIPO (World Intellectual Property Organization) • EUIPO (European Union Intellectual Property Office) 2. Develop an API endpoint to retrieve patents: • Allow searches by company name, domain, or registration ID. • Fetch patent titles, descriptions, filing dates, inventors, and legal statuses. 3. Integrate patent data into company profiles: • Display the number of patents in the Profit Vision section. • Include a detailed list of patents for premium users. 4. Make patents a premium datapoint: • Restrict detailed patent information to paid subscribers. • Allow basic patent count visibility for all users. 5. Ensure scheduled updates: • Refresh patent records periodically to include newly filed patents. 6. Provide filtering & search capabilities: • Allow users to search companies based on patent ownership. • Enable filtering by patent category, technology, or region.
Julien Le Coupanec 7 days ago
Datapoints
Add a PageRank key for SEO insights
We need to add a PageRank-related datapoint to the company profiles, allowing users to evaluate how well a company’s website is indexed on Google. This will help determine a website’s authority and SEO strength. To achieve this, we must find external APIs or alternative ways to retrieve this data. 🔹 Why? • Helps gauge a company’s online visibility & authority. • Adds a valuable SEO metric to company profiles. • Enables better company segmentation based on digital presence. 🔹 How it works? 1. Find an API or method to retrieve PageRank-like data: • Since Google no longer provides official PageRank scores, explore alternative SEO scoring APIs like: • Moz Domain Authority • Ahrefs Domain Rating • Majestic Trust Flow • Alternatively, analyze backlink counts & indexed pages to estimate ranking strength. 2. Integrate this data into the ProfitZone section: • Store the SEO authority score for each company. • Show it in company profiles with an explanation of its meaning. 3. Provide API access for PageRank data: • Allow users to query PageRank insights via our API. 4. Enable filtering & segmentation: • Let users filter/search companies based on their SEO ranking. 5. Ensure regular updates: • Implement scheduled data refreshes to keep rankings accurate. 6. Optimize query costs: • If using paid APIs, batch requests efficiently to minimize costs. • Consider scraping public SEO data where possible.
Julien Le Coupanec 7 days ago
Features
Add a PageRank key for SEO insights
We need to add a PageRank-related datapoint to the company profiles, allowing users to evaluate how well a company’s website is indexed on Google. This will help determine a website’s authority and SEO strength. To achieve this, we must find external APIs or alternative ways to retrieve this data. 🔹 Why? • Helps gauge a company’s online visibility & authority. • Adds a valuable SEO metric to company profiles. • Enables better company segmentation based on digital presence. 🔹 How it works? 1. Find an API or method to retrieve PageRank-like data: • Since Google no longer provides official PageRank scores, explore alternative SEO scoring APIs like: • Moz Domain Authority • Ahrefs Domain Rating • Majestic Trust Flow • Alternatively, analyze backlink counts & indexed pages to estimate ranking strength. 2. Integrate this data into the ProfitZone section: • Store the SEO authority score for each company. • Show it in company profiles with an explanation of its meaning. 3. Provide API access for PageRank data: • Allow users to query PageRank insights via our API. 4. Enable filtering & segmentation: • Let users filter/search companies based on their SEO ranking. 5. Ensure regular updates: • Implement scheduled data refreshes to keep rankings accurate. 6. Optimize query costs: • If using paid APIs, batch requests efficiently to minimize costs. • Consider scraping public SEO data where possible.
Julien Le Coupanec 7 days ago
Features
Create an API for VAT numbers and integrate with company profiles
We could create an API for VAT numbers similar to services like vatlayer.com, allowing users to retrieve the VAT number of a company by sending its domain name. This API would also integrate into the Profit Vision of company profiles, automatically displaying the VAT number when available. Additionally, we could leverage AI to extract VAT numbers from Terms & Conditions pages on company websites. 🔹 Why? • Provides easy access to VAT numbers for users looking to verify company identities. • Improves company profile enrichment by adding verified VAT information. • Automates VAT number extraction from Terms & Conditions pages using AI, increasing accuracy. 🔹 How it works? 1. Create a VAT number lookup API: • Allow users to send a domain name (e.g., “example.com”) and get the VAT number of the corresponding company. • Integrate with VAT validation services to ensure correctness. 2. Integrate the VAT number into company profiles: • Automatically fetch and display the VAT number in the Profit Vision section of company profiles when available. 3. Leverage AI to extract VAT numbers from Terms & Conditions pages: • Use AI-based document processing to scan and extract VAT numbers from publicly available Terms pages. • Add a secondary data source for VAT numbers to complement the API. 4. Implement an intelligent search feature: • Ensure users can easily query companies by VAT number or domain. 5. Ensure data accuracy: • Implement validation checks to confirm the fetched VAT number matches the domain/company. 6. Provide real-time updates: • Regularly update the database to reflect changes in VAT information. 7. Monitor performance and optimize the AI system for accurate extraction from web pages.
Julien Le Coupanec 7 days ago
Features
Create an API for VAT numbers and integrate with company profiles
We could create an API for VAT numbers similar to services like vatlayer.com, allowing users to retrieve the VAT number of a company by sending its domain name. This API would also integrate into the Profit Vision of company profiles, automatically displaying the VAT number when available. Additionally, we could leverage AI to extract VAT numbers from Terms & Conditions pages on company websites. 🔹 Why? • Provides easy access to VAT numbers for users looking to verify company identities. • Improves company profile enrichment by adding verified VAT information. • Automates VAT number extraction from Terms & Conditions pages using AI, increasing accuracy. 🔹 How it works? 1. Create a VAT number lookup API: • Allow users to send a domain name (e.g., “example.com”) and get the VAT number of the corresponding company. • Integrate with VAT validation services to ensure correctness. 2. Integrate the VAT number into company profiles: • Automatically fetch and display the VAT number in the Profit Vision section of company profiles when available. 3. Leverage AI to extract VAT numbers from Terms & Conditions pages: • Use AI-based document processing to scan and extract VAT numbers from publicly available Terms pages. • Add a secondary data source for VAT numbers to complement the API. 4. Implement an intelligent search feature: • Ensure users can easily query companies by VAT number or domain. 5. Ensure data accuracy: • Implement validation checks to confirm the fetched VAT number matches the domain/company. 6. Provide real-time updates: • Regularly update the database to reflect changes in VAT information. 7. Monitor performance and optimize the AI system for accurate extraction from web pages.
Julien Le Coupanec 7 days ago
Features
Integrate Wikidata as a data source and create Wikidata profiles for companies
Wikidata contains a vast amount of structured company information, including industry classifications, founding dates, key people, and headquarters locations. We need to process this source and create Wikidata profiles for every company we can match in our database. 🔹 Why? • Expands data coverage with additional structured details. • Improves company profiles with verified public data. • Enhances search capabilities and enrichment by linking Wikidata identifiers. 🔹 How it works? 1. Extract company data from Wikidata: • Query Wikidata for companies matching our dataset. • Extract key information (founding year, industry, parent company, etc.). • Store Wikidata identifiers in our database. 2. Create Wikidata profiles for matched companies: • Display Wikidata data alongside other sources in company profiles. • Allow users to cross-check and validate information. 3. Handle updates & synchronization: • Implement scheduled updates to refresh data periodically. • Detect new companies added to Wikidata and integrate them. 4. Validate data accuracy: • Ensure company names and identifiers match correctly before merging data. • Set up manual review options for conflicting records. 5. Provide an API endpoint for accessing Wikidata-enriched profiles.
Julien Le Coupanec 7 days ago
Datapoints
Integrate Wikidata as a data source and create Wikidata profiles for companies
Wikidata contains a vast amount of structured company information, including industry classifications, founding dates, key people, and headquarters locations. We need to process this source and create Wikidata profiles for every company we can match in our database. 🔹 Why? • Expands data coverage with additional structured details. • Improves company profiles with verified public data. • Enhances search capabilities and enrichment by linking Wikidata identifiers. 🔹 How it works? 1. Extract company data from Wikidata: • Query Wikidata for companies matching our dataset. • Extract key information (founding year, industry, parent company, etc.). • Store Wikidata identifiers in our database. 2. Create Wikidata profiles for matched companies: • Display Wikidata data alongside other sources in company profiles. • Allow users to cross-check and validate information. 3. Handle updates & synchronization: • Implement scheduled updates to refresh data periodically. • Detect new companies added to Wikidata and integrate them. 4. Validate data accuracy: • Ensure company names and identifiers match correctly before merging data. • Set up manual review options for conflicting records. 5. Provide an API endpoint for accessing Wikidata-enriched profiles.
Julien Le Coupanec 7 days ago
Datapoints
Retrieve and update follower count for social networks
We need to fetch the number of followers for each company’s social media accounts. This process should: 1. Automatically retrieve follower counts when a social link is added. 2. Provide a script to fetch and update follower data for all companies. 3. Identify and remove obsolete or broken social media links. 4. Allow filtering to update specific social platforms selectively. 🔹 Why? • Helps enrich company profiles with valuable engagement metrics. • Keeps social media links up to date by removing inactive profiles. • Improves search relevance and data quality in our system. 🔹 How it works? 1. Develop a process to fetch follower counts: • Use proxies to bypass restrictions on scraping. • Implement APIs where possible (e.g., Twitter/X, LinkedIn, Instagram). • Fallback to scraping when no API is available. 2. Create a background job that triggers when a social profile is added: • Fetch the follower count and store it in the company profile. 3. Build a standalone script to: • Retrieve follower data for all companies. • Allow selective fetching (e.g., update only LinkedIn or Instagram). • Detect and remove broken social links automatically. 4. Store the last updated date for each social network to optimize re-fetching. 5. Run validation tests to ensure the script correctly updates social data.
Julien Le Coupanec 7 days ago
Datapoints
Retrieve and update follower count for social networks
We need to fetch the number of followers for each company’s social media accounts. This process should: 1. Automatically retrieve follower counts when a social link is added. 2. Provide a script to fetch and update follower data for all companies. 3. Identify and remove obsolete or broken social media links. 4. Allow filtering to update specific social platforms selectively. 🔹 Why? • Helps enrich company profiles with valuable engagement metrics. • Keeps social media links up to date by removing inactive profiles. • Improves search relevance and data quality in our system. 🔹 How it works? 1. Develop a process to fetch follower counts: • Use proxies to bypass restrictions on scraping. • Implement APIs where possible (e.g., Twitter/X, LinkedIn, Instagram). • Fallback to scraping when no API is available. 2. Create a background job that triggers when a social profile is added: • Fetch the follower count and store it in the company profile. 3. Build a standalone script to: • Retrieve follower data for all companies. • Allow selective fetching (e.g., update only LinkedIn or Instagram). • Detect and remove broken social links automatically. 4. Store the last updated date for each social network to optimize re-fetching. 5. Run validation tests to ensure the script correctly updates social data.
Julien Le Coupanec 7 days ago
Datapoints
Enable role management for team members in settings
We need to allow team owners or admins to change user roles within their team from the application settings. This feature will enable assigning roles such as admin or user, ensuring proper access control. 🔹 Why? • Gives teams better control over user permissions. • Allows role delegation without requiring manual support intervention. • Improves security by restricting sensitive actions to admins only. 🔹 How it works? 1. Add a role management section in the team settings. 2. Define available roles: • Admin → Can manage billing, settings, and user roles. • User → Can access the platform but has limited permissions. 3. Implement role change functionality: • Only admins can modify roles of other team members. • Confirmation prompts before changing a role. • Prevent users from removing the last admin to avoid orphaned teams. 4. Update API & database to handle role changes securely. 5. Ensure UI updates dynamically when roles are modified. 6. Add security checks & tests to prevent unauthorized role changes.
Julien Le Coupanec 7 days ago
Features
Enable role management for team members in settings
We need to allow team owners or admins to change user roles within their team from the application settings. This feature will enable assigning roles such as admin or user, ensuring proper access control. 🔹 Why? • Gives teams better control over user permissions. • Allows role delegation without requiring manual support intervention. • Improves security by restricting sensitive actions to admins only. 🔹 How it works? 1. Add a role management section in the team settings. 2. Define available roles: • Admin → Can manage billing, settings, and user roles. • User → Can access the platform but has limited permissions. 3. Implement role change functionality: • Only admins can modify roles of other team members. • Confirmation prompts before changing a role. • Prevent users from removing the last admin to avoid orphaned teams. 4. Update API & database to handle role changes securely. 5. Ensure UI updates dynamically when roles are modified. 6. Add security checks & tests to prevent unauthorized role changes.
Julien Le Coupanec 7 days ago
Features
Generate website description and tagline in AI-powered company profiles
We need to automatically generate the website description and tagline for companies within the AI-powered profiles in Power. This will enhance company insights by providing concise and meaningful summaries of what each company does, based on its website content. 🔹 Why? • Improves profile completeness with AI-generated descriptions. • Helps users quickly understand what a company does. • Enhances data consistency by standardizing descriptions and taglines. 🔹 How it works? 1. Extract relevant content from the company’s website: • Use meta descriptions, headings, and key content to understand the company’s mission. • Identify slogans, taglines, or unique value propositions. 2. Process data with an AI model: • Summarize website content into a short, clear description. • Generate a concise tagline that reflects the company’s focus. 3. Store the generated text in the company’s AI profile in Power. 4. Validate AI-generated content to ensure accuracy and relevance. 5. Allow manual overrides if necessary, enabling adjustments when the AI output is incorrect.
Julien Le Coupanec 7 days ago
Datapoints
Generate website description and tagline in AI-powered company profiles
We need to automatically generate the website description and tagline for companies within the AI-powered profiles in Power. This will enhance company insights by providing concise and meaningful summaries of what each company does, based on its website content. 🔹 Why? • Improves profile completeness with AI-generated descriptions. • Helps users quickly understand what a company does. • Enhances data consistency by standardizing descriptions and taglines. 🔹 How it works? 1. Extract relevant content from the company’s website: • Use meta descriptions, headings, and key content to understand the company’s mission. • Identify slogans, taglines, or unique value propositions. 2. Process data with an AI model: • Summarize website content into a short, clear description. • Generate a concise tagline that reflects the company’s focus. 3. Store the generated text in the company’s AI profile in Power. 4. Validate AI-generated content to ensure accuracy and relevance. 5. Allow manual overrides if necessary, enabling adjustments when the AI output is incorrect.
Julien Le Coupanec 7 days ago
Datapoints
Enhance stock index data for company profiles
A client has requested more detailed stock index information in company profiles, particularly for major stock indices such as S&P 500, NYSE, NASDAQ, CAC 40, Dow Jones, Nikkei 225, FTSE 100, DAX 40, Shanghai Composite, Hang Seng Index, and BSE Index. While the current data is useful, more precise financial details would improve its value. 🔹 Why? • Helps users analyze public companies more effectively. • Enhances financial data visibility, especially for North American & European markets. • Provides a competitive edge by offering more detailed stock insights. 🔹 How it works? 1. Identify missing or incomplete stock data in company profiles. 2. Enhance stock index classification: • Ensure each public company is correctly linked to its respective index(es). • Store historical index membership where relevant. 3. Expand financial details for tracked companies: • Add stock symbol (ticker), exchange, market cap, share price trends, and other key financial metrics. • Ensure real-time or near real-time updates where applicable. 4. Optimize search & filtering by stock index: • Allow users to search or segment companies based on their stock index. • Improve index-based sorting & recommendations. 5. Run a validation script: • Ensure no major listed company is missing from relevant indices. • Clean incorrect or outdated stock data. 6. Make stock index data more visible in company profiles for better usability.
Julien Le Coupanec 7 days ago
Datapoints
Enhance stock index data for company profiles
A client has requested more detailed stock index information in company profiles, particularly for major stock indices such as S&P 500, NYSE, NASDAQ, CAC 40, Dow Jones, Nikkei 225, FTSE 100, DAX 40, Shanghai Composite, Hang Seng Index, and BSE Index. While the current data is useful, more precise financial details would improve its value. 🔹 Why? • Helps users analyze public companies more effectively. • Enhances financial data visibility, especially for North American & European markets. • Provides a competitive edge by offering more detailed stock insights. 🔹 How it works? 1. Identify missing or incomplete stock data in company profiles. 2. Enhance stock index classification: • Ensure each public company is correctly linked to its respective index(es). • Store historical index membership where relevant. 3. Expand financial details for tracked companies: • Add stock symbol (ticker), exchange, market cap, share price trends, and other key financial metrics. • Ensure real-time or near real-time updates where applicable. 4. Optimize search & filtering by stock index: • Allow users to search or segment companies based on their stock index. • Improve index-based sorting & recommendations. 5. Run a validation script: • Ensure no major listed company is missing from relevant indices. • Clean incorrect or outdated stock data. 6. Make stock index data more visible in company profiles for better usability.
Julien Le Coupanec 7 days ago
Datapoints
Enable company segmentation by language
Currently, we cannot segment companies by language in our interface or search API. 🔹 Why? • Allows targeted segmentation based on the primary language of a company. • Improves search accuracy when filtering by language. 🔹 How it works? 1. Extract language information: • Analyze company websites to detect their primary language. • Check metadata (e.g., HTML lang attribute, content language, and text analysis). 2. Add language segmentation to the API: • Enable users to filter companies by language when searching. • Store detected language data in the company profile. 4. Update the UI to support language-based filtering. 5. Test language detection accuracy and refine the system as needed.
Julien Le Coupanec 7 days ago
Features
Enable company segmentation by language
Currently, we cannot segment companies by language in our interface or search API. 🔹 Why? • Allows targeted segmentation based on the primary language of a company. • Improves search accuracy when filtering by language. 🔹 How it works? 1. Extract language information: • Analyze company websites to detect their primary language. • Check metadata (e.g., HTML lang attribute, content language, and text analysis). 2. Add language segmentation to the API: • Enable users to filter companies by language when searching. • Store detected language data in the company profile. 4. Update the UI to support language-based filtering. 5. Test language detection accuracy and refine the system as needed.
Julien Le Coupanec 7 days ago
Features
Remove Blogger and Quantcast from code and company profiles
The technologies Blogger and Quantcast have been removed and should no longer be detected or stored. We need to clean the codebase and ensure no company profiles contain these technologies. 🔹 Why? • Prevents outdated or incorrect technology data in company profiles. • Keeps the codebase clean and optimized by removing unused logic. • Ensures search results and filters remain accurate. 🔹 How it works? 1. Remove Blogger and Quantcast detection logic from the codebase. 2. Scan all company profiles to identify any instances of these technologies. 3. Run a cleanup script to remove Blogger and Quantcast from affected profiles. 4. Ensure API responses no longer include these technologies. 5. Add validation to prevent them from being added again in the future.
Julien Le Coupanec 7 days ago
Datapoints
Remove Blogger and Quantcast from code and company profiles
The technologies Blogger and Quantcast have been removed and should no longer be detected or stored. We need to clean the codebase and ensure no company profiles contain these technologies. 🔹 Why? • Prevents outdated or incorrect technology data in company profiles. • Keeps the codebase clean and optimized by removing unused logic. • Ensures search results and filters remain accurate. 🔹 How it works? 1. Remove Blogger and Quantcast detection logic from the codebase. 2. Scan all company profiles to identify any instances of these technologies. 3. Run a cleanup script to remove Blogger and Quantcast from affected profiles. 4. Ensure API responses no longer include these technologies. 5. Add validation to prevent them from being added again in the future.
Julien Le Coupanec 7 days ago
Datapoints
Display apps data aesthetically in company profiles
The apps key in company profiles contains valuable information, such as iOS and Android applications associated with the company. We need to visually enhance how this data is displayed in the UI to make it clear, structured, and user-friendly. 🔹 Why? • Provides better visibility of a company’s mobile presence. • Enhances profile usability by making app data easily accessible. • Improves lead enrichment by showcasing mobile-related insights. 🔹 How it works? 1. Retrieve APPS data from the company’s JSON profile. 2. Design a structured UI component to display app information: • Separate sections for iOS & Android apps. • Display app name, icon, and store link. • Optionally, show ratings or reviews if available. 3. Ensure responsive display for different screen sizes. 4. Optimize data loading to prevent performance issues. 5. Implement sorting/filtering if a company has multiple apps. 6. Test across various companies to verify correct rendering.
Julien Le Coupanec 11 days ago
Datapoints
Display apps data aesthetically in company profiles
The apps key in company profiles contains valuable information, such as iOS and Android applications associated with the company. We need to visually enhance how this data is displayed in the UI to make it clear, structured, and user-friendly. 🔹 Why? • Provides better visibility of a company’s mobile presence. • Enhances profile usability by making app data easily accessible. • Improves lead enrichment by showcasing mobile-related insights. 🔹 How it works? 1. Retrieve APPS data from the company’s JSON profile. 2. Design a structured UI component to display app information: • Separate sections for iOS & Android apps. • Display app name, icon, and store link. • Optionally, show ratings or reviews if available. 3. Ensure responsive display for different screen sizes. 4. Optimize data loading to prevent performance issues. 5. Implement sorting/filtering if a company has multiple apps. 6. Test across various companies to verify correct rendering.
Julien Le Coupanec 11 days ago
Datapoints
Ensure all company descriptions are fully translated & enforce auto-translation
We need to ensure that all company descriptions in our database are fully translated and that the translation system is always active when processing descriptions. A script should be executed to translate all existing descriptions, ensuring no company remains untranslated. 🔹 Why? • Prevents incomplete or missing translations. • Ensures global accessibility of company profiles. • Maintains data consistency across all entries. 🔹 How it works? 1. Scan the database to identify company descriptions that are not translated. 2. Run a script that: • Uses the translation system to process all missing descriptions. • Updates database records without overwriting existing translations. 3. Modify the translation pipeline to: • Always enforce automatic translation whenever a description is processed. • Prevent new company descriptions from being stored without translation. 4. Add validation tests to confirm: • Every company description is correctly translated. • The translation system is always applied when needed. 5. Monitor and verify the translations to ensure accuracy and completeness.
Julien Le Coupanec 11 days ago
Datapoints
Ensure all company descriptions are fully translated & enforce auto-translation
We need to ensure that all company descriptions in our database are fully translated and that the translation system is always active when processing descriptions. A script should be executed to translate all existing descriptions, ensuring no company remains untranslated. 🔹 Why? • Prevents incomplete or missing translations. • Ensures global accessibility of company profiles. • Maintains data consistency across all entries. 🔹 How it works? 1. Scan the database to identify company descriptions that are not translated. 2. Run a script that: • Uses the translation system to process all missing descriptions. • Updates database records without overwriting existing translations. 3. Modify the translation pipeline to: • Always enforce automatic translation whenever a description is processed. • Prevent new company descriptions from being stored without translation. 4. Add validation tests to confirm: • Every company description is correctly translated. • The translation system is always applied when needed. 5. Monitor and verify the translations to ensure accuracy and completeness.
Julien Le Coupanec 11 days ago
Datapoints
Integrate with Clay to provide API access inside their platform
We need to build an integration with Clay, allowing users to access our endpoints, data, and algorithms directly inside their workflows. This will enable Clay users to enrich their contact and company data seamlessly within their platform. 🔹 Why? • Expands our reach and usability by integrating with an existing automation tool. • Allows Clay users to access our insights without switching platforms. • Provides seamless lead enrichment, company intelligence, and segmentation. 🔹 How it works? 1. Understand Clay’s API and integration requirements. 2. Expose our endpoints inside Clay to allow: • Company enrichment from domain names. • Similarity searches to find related businesses. • Technology detection for tracking SaaS adoption. • Real-time Signals for dynamic updates on companies. 3. Develop a plug-and-play integration for Clay users. 4. Ensure authentication via API keys for secure access. 5. Test the integration thoroughly before launch.
Julien Le Coupanec 11 days ago
Integrations
Integrate with Clay to provide API access inside their platform
We need to build an integration with Clay, allowing users to access our endpoints, data, and algorithms directly inside their workflows. This will enable Clay users to enrich their contact and company data seamlessly within their platform. 🔹 Why? • Expands our reach and usability by integrating with an existing automation tool. • Allows Clay users to access our insights without switching platforms. • Provides seamless lead enrichment, company intelligence, and segmentation. 🔹 How it works? 1. Understand Clay’s API and integration requirements. 2. Expose our endpoints inside Clay to allow: • Company enrichment from domain names. • Similarity searches to find related businesses. • Technology detection for tracking SaaS adoption. • Real-time Signals for dynamic updates on companies. 3. Develop a plug-and-play integration for Clay users. 4. Ensure authentication via API keys for secure access. 5. Test the integration thoroughly before launch.
Julien Le Coupanec 11 days ago
Integrations
Limit the number of WhatsApp, Line, and other contact entries per company
We need to set a cap on the number of WhatsApp, Line, and similar contact entries per company. Some companies, like microdobem.com.br, have an excessive number of contacts, which is not expected behavior. We must clean existing data and enforce a hard limit to prevent such cases in the future. 🔹 Why? • Prevents data overload and ensures a clean, structured database. • Avoids irrelevant or duplicate contact entries cluttering company profiles. • Enhances data reliability by maintaining a reasonable contact count. 🔹 How it works? 1. Define a maximum number of allowed contacts per platform (e.g., WhatsApp: 3, Line: 3, Telegram: 3). 2. Create a script to clean existing data: • Identify companies exceeding the limit. • Remove excess contacts, keeping only the most relevant ones (e.g., verified, most used, or first added). 3. Modify the indexing pipeline to: • Prevent storing more than the allowed limit per company. • Ensure duplicate numbers are merged instead of being added as separate entries. 4. Enforce validation rules in the API to block excessive contacts. 5. Add backend tests to confirm: • The cap is respected across all processes. • The cleanup script successfully trims excessive contacts.
Julien Le Coupanec 11 days ago
Datapoints
Limit the number of WhatsApp, Line, and other contact entries per company
We need to set a cap on the number of WhatsApp, Line, and similar contact entries per company. Some companies, like microdobem.com.br, have an excessive number of contacts, which is not expected behavior. We must clean existing data and enforce a hard limit to prevent such cases in the future. 🔹 Why? • Prevents data overload and ensures a clean, structured database. • Avoids irrelevant or duplicate contact entries cluttering company profiles. • Enhances data reliability by maintaining a reasonable contact count. 🔹 How it works? 1. Define a maximum number of allowed contacts per platform (e.g., WhatsApp: 3, Line: 3, Telegram: 3). 2. Create a script to clean existing data: • Identify companies exceeding the limit. • Remove excess contacts, keeping only the most relevant ones (e.g., verified, most used, or first added). 3. Modify the indexing pipeline to: • Prevent storing more than the allowed limit per company. • Ensure duplicate numbers are merged instead of being added as separate entries. 4. Enforce validation rules in the API to block excessive contacts. 5. Add backend tests to confirm: • The cap is respected across all processes. • The cleanup script successfully trims excessive contacts.
Julien Le Coupanec 11 days ago
Datapoints
Detect Shopify+ and ensure revenue accuracy
We need to add Shopify+ detection to our technology tracking system. Shopify+ is a high-end e-commerce solution used by businesses generating significant revenue. Identifying Shopify+ sites will also help us validate revenue estimates, as no Shopify+ site operates at low revenue levels. 🔹 Why? • Enables targeting of high-revenue e-commerce businesses. • Improves accuracy of revenue estimation by setting a revenue floor for Shopify+ sites. • Enhances lead qualification for sales, marketing, and investment analysis. 🔹 How it works? 1. Detect Shopify+ presence by: • Checking meta tags, headers, and unique identifiers in the website’s source code. • Scraping Shopify+ checkout and admin patterns. • Using DNS records and third-party indicators. 2. Assign the technology tag Shopify+ in company profiles. 3. Enforce revenue validation: • If Shopify+ is detected, ensure minimum revenue is correctly estimated. • Apply a revenue floor rule, flagging anomalies where revenue appears too low. 4. Batch process existing company data to detect Shopify+ in the current dataset. 5. Improve API & UI filtering: • Allow users to filter companies using Shopify+. • Highlight Shopify+ businesses as high-revenue potential.
Julien Le Coupanec 11 days ago
Datapoints
Detect Shopify+ and ensure revenue accuracy
We need to add Shopify+ detection to our technology tracking system. Shopify+ is a high-end e-commerce solution used by businesses generating significant revenue. Identifying Shopify+ sites will also help us validate revenue estimates, as no Shopify+ site operates at low revenue levels. 🔹 Why? • Enables targeting of high-revenue e-commerce businesses. • Improves accuracy of revenue estimation by setting a revenue floor for Shopify+ sites. • Enhances lead qualification for sales, marketing, and investment analysis. 🔹 How it works? 1. Detect Shopify+ presence by: • Checking meta tags, headers, and unique identifiers in the website’s source code. • Scraping Shopify+ checkout and admin patterns. • Using DNS records and third-party indicators. 2. Assign the technology tag Shopify+ in company profiles. 3. Enforce revenue validation: • If Shopify+ is detected, ensure minimum revenue is correctly estimated. • Apply a revenue floor rule, flagging anomalies where revenue appears too low. 4. Batch process existing company data to detect Shopify+ in the current dataset. 5. Improve API & UI filtering: • Allow users to filter companies using Shopify+. • Highlight Shopify+ businesses as high-revenue potential.
Julien Le Coupanec 11 days ago
Datapoints