Large technographic dataset
Track 54K+ technologies across 86M+ companies, with technology name, timestamps, category, description, pricing data, and source details included for each technology record.
PredictLeads Technographics is a company intelligence dataset focused on the technologies organizations use. It is delivered through APIs, flat files, webhooks, and MCP, and is designed to help teams discover, monitor, and act on technology stack signals across large numbers of companies.
The product combines detections from company websites, script tags, DNS records, IP ranges, cookies, and job descriptions. PredictLeads says it tracks 54K+ technologies across 86M+ companies and includes source and methodology details for each detection, along with first-seen and last-seen timestamps, category data, and technology relationships.
Track 54K+ technologies across 86M+ companies, with technology name, timestamps, category, description, pricing data, and source details included for each technology record.
Detect technologies from multiple signals such as script tags, DNS records, IP ranges, cookies, and job descriptions to improve coverage and reduce missed detections.
Review first-seen and last-seen timestamps for each detection to understand when a technology appeared, how long it persisted, and whether it is still present.
Use category and parent-category information to organize tools and filter technologies by segment or product family.
Access technology relationships that show which technologies imply, require, or exclude others, helping teams understand stack dependencies and compatibility.
Connect the dataset to AI agents through MCP for structured, real-time retrieval of technology insights and downstream actions.
Build lists of companies using a specific stack, such as HubSpot, Salesforce, or Marketo, by querying the technology discovery endpoint.
Track first-seen and last-seen dates to watch adoption curves, identify emerging tools, and spot technologies that are growing or fading.
Compare adoption across competing tools within the same category to understand market share dynamics and replacement patterns.
Use stack data alongside category and relationship fields to identify likely dependencies, complementary tools, and compatibility constraints.
Feed structured technology insights into AI systems through MCP so agents can retrieve current signals during prospecting, research, or enrichment workflows.
PredictLeads technographic data identifies the technologies companies use and is delivered through APIs, flat files, webhooks, and an MCP server. The technologies page also notes that you can access a technology discovery endpoint to find companies using a specific tool.
The source pages show data pulled from websites, script tags, DNS records, IP ranges, cookies, and job descriptions. The technologies page also says each technology includes sources and methodology for transparency.
The pricing page says the first 100 API calls each month are free, with usage beyond that billed on a pay-as-you-go basis. It also states that flat files and webhook access are available.
The product is positioned for company intelligence, market research, competitive analysis, sales, and AI workflows that need structured company data. It is also described as being available via MCP for agentic systems.
The technologies page describes point-in-time detection data, including first and last seen timestamps, technology category information, pricing data, and technology relationships such as implied, required, or excluded tools.
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