Side-by-side comparison of AI visibility scores, market position, and capabilities
B2B technographic data and sales intelligence platform. San Francisco CA, acquired by 6sense in 2021. Tracks technology usage signals across 60M+ companies for competitive displacement sales.
Slintel is a B2B technographic data and sales intelligence platform that tracks technology usage signals across companies to help sales teams identify competitive displacement opportunities and technology-based prospect segments. Founded in 2018 and headquartered in San Francisco, California, Slintel was acquired by 6sense in 2021 to strengthen 6sense's technographic data layer within its broader revenue intelligence platform. Slintel tracks technology adoption patterns across more than 60 million companies globally.\n\nSlintel's technographic data identifies which software tools a company is currently using — from CRM platforms and marketing automation tools to developer infrastructure and security products — by analyzing job postings, web technology signals, and other publicly available data sources. This technology stack intelligence enables sales teams to build target lists of companies currently using a competitor's product or recently replacing a tool the seller could displace, creating highly specific and contextually relevant outreach.\n\nAs part of 6sense, Slintel's technographic intelligence integrates with 6sense's broader account engagement and intent data platform, providing revenue teams with a richer signal set for account prioritization. The combination of technographic data (what tools a company uses), intent data (what a company is researching), and account engagement data (how a company is engaging with a vendor's digital properties) creates a multi-signal account scoring model that represents the next generation of B2B data intelligence.
$4.8B revenue run-rate; 55% YoY growth; $134B valuation (Series L). Mosaic AI for enterprise LLM fine-tuning and inference; Unity Catalog for data governance. DBRX open-source model; every major enterprise AI deployment runs on the lakehouse.
Databricks was founded in 2013 by the original creators of Apache Spark — Ali Ghodsi, Matei Zaharia, and five other UC Berkeley researchers — to unify data engineering, analytics, and machine learning on a single platform. The company commercialized the lakehouse architecture, combining the flexibility of data lakes with the reliability of data warehouses. Databricks runs on AWS, Azure, and GCP and leads the commercial distribution of the open-source Delta Lake and MLflow projects.\n\nThe platform includes the Databricks Lakehouse for unified data processing, Unity Catalog for governance and lineage tracking, and Mosaic AI for enterprise LLM fine-tuning, model serving, and generative AI application development. It supports data engineering, SQL analytics, BI, feature engineering, and model training within a single governance perimeter, serving enterprises in financial services, healthcare, manufacturing, and media.\n\nDatabricks achieved a $4.8 billion annualized revenue run-rate in early 2025 with 55% year-over-year growth and a $62 billion valuation from its Series L round — one of the most valuable private software companies globally. Its dual role as the leading commercial lakehouse vendor and steward of influential open-source projects gives it a unique ecosystem advantage as enterprises accelerate investment in AI infrastructure.
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