data-lineage
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The Data Catalog That Learned to Answer Back
Born from LinkedIn’s metadata crisis, DataHub is turning the humble data catalog into a live map for humans and AI agents. The clever part is not collecting more data. It is remembering what the data means.
Your Data Has a Memory Problem. Select Star Built the Map.
Select Star turns the warehouse, dashboards and half-remembered business rules into a searchable map. For teams buried under tables, its signature trick is not collecting more metadata - it is making the useful context hard to miss.
Bigeye Watches the Data Your AI Forgot to Question
Bigeye began by catching broken tables before they reached the boardroom. Now it wants to watch the agents reading them, too - a useful expansion for enterprises, and a lot of machinery for everyone else.
CastorDoc Turned the Data Catalog Into the Office Help Desk
The catalog once known as CastorDoc makes a persuasive case that governance works better when it feels like search, not paperwork. Its acquisition by Coalesce gives the friendly front door a much bigger engine room.
Secoda Put a Search Bar on the Data Swamp
Every company says its data is valuable. Secoda tackles the less glamorous problem: helping people find it, understand it, trust it, and stop asking the same analyst where the revenue table lives.
Collibra Wants to Be the Air-Traffic Control for Your Company's AI
The Belgian data-governance pioneer spent 18 years teaching companies what their data means. Now it is betting that AI agents need the same lesson - plus a control tower.
Nishant Doshi Has Spent 20 Years Following Data - Now the Data Is Learning to Move Alone
The Cyberhaven CEO has built and sold two companies by noticing where enterprise software was heading. His latest bet is that protecting files is no longer enough when data travels through people, prompts, and autonomous agents.
Philip Dutton Drew a Map of the Data Nobody Wanted to Explain
Before AI could explain itself, someone had to explain the data beneath it. Philip Dutton spent two decades turning institutional spaghetti into a map people can question, test and trust.
The $247,500 Map That Tells Banks Where Their Data Will Break
Most companies document data after the damage is done. Solidatus sells banks a living map of what changed, what will break next, and who has to explain it to the regulator.
Abhi Sharma
For Abhi Sharma, the useful map is never the static one. From a college navigation experiment to Relyance AI's moving graph of enterprise data, his career has followed one question: can software reveal what people cannot see?
Velum Labs
Velum Labs is a Y Combinator-backed San Francisco startup building an operating system for data quality. Its platform continuously watches a company's data stack, catches when metrics and definitions diverge, traces the root cause through query lineage, proposes automated fixes, and then writes enforceable data contracts so the same break does not recur. Founded in 2025 by Chilean-born childhood friends Benjamin Munoz-Cerro (CEO) and Alen Rubilar-Munoz (CTO), the company is already in production at regulated fintechs monitoring 200+ tables tied to more than $1B in assets.
Astronomer
Astronomer is a New York-based data infrastructure company and the commercial force behind Apache Airflow, the open-source standard for data orchestration. Its flagship product, Astro, is a fully managed, cloud-native platform that lets data teams build, run, and observe data pipelines at scale, and its Astro Observe layer extends that into data operations and observability. Astronomer employs a large share of Airflow's core committers, serves 700+ enterprise customers, and raised a $93M Series D in May 2025 to power orchestration for enterprise AI workloads.
ORION Security
ORION Security is an AI-native data loss prevention (DLP) company that protects enterprises from data leaks without relying on manually written policies. Founded in 2024 by Nitay Milner and Jonathan Kreiner, ORION uses large language models and specialized AI agents to map how data normally flows across SaaS, email, cloud, endpoints, and AI tools, then analyzes content sensitivity, user identity, behavioral intent, and data lineage to catch exfiltration and insider threats in real time. The platform targets the three core sources of data loss - human error, malicious insiders, and external attackers - while cutting the false positives and maintenance burden that plague legacy DLP.
Promethium
Promethium is a Menlo Park-based enterprise data company that builds an Instant Data Fabric - an agentic platform designed to give business users, analysts, and AI agents trusted, self-service access to data across hundreds of sources without first moving or centralizing it. Its federated query engine, 360 Context Engine, and conversational data-answer agent Mantra translate natural-language questions into governed SQL, metadata, lineage, and visualizations. Founded in 2018 by Kaycee Lai and now led by CEO Prat Moghe, the company has raised about $34.5 million to date, including a $26 million Series A led by Insight Partners.
Cyberhaven
Cyberhaven is a data security company that protects enterprises from data exfiltration and insider risk by tracing how information moves rather than just where it sits. Founded in 2016 by five PhD researchers with roots in the DARPA Cyber Grand Challenge, the company built a proprietary 'data lineage' engine and an AI layer, Linea AI, that combines Data Loss Prevention (DLP), Data Security Posture Management (DSPM), Insider Risk Management, and AI security into one platform. Reaching a $1 billion valuation in April 2025 after a $100M Series D, Cyberhaven serves customers such as Snowflake, Motorola, Reddit, and major law firms.
DvSum
DvSum is a Sunnyvale, California data intelligence company founded in 2014 by Aashish Singhvi. Its cloud platform unifies data catalog, data quality, data governance and data lineage into a single automated system, and layers AI agents on top - including a 'Talk to Your Data' conversational agent (CADDI) that lets business users query their data in plain language. More recently DvSum has extended its agentic AI approach into telecom with an Active Network Intelligence stack (AURA) that helps operators detect, diagnose and resolve network issues before subscribers call.
Collate
Collate is the company behind OpenMetadata, the fast-growing open source project for unified data discovery, observability, and governance. Founded by Apache open source veterans Suresh Srinivas and Sriharsha Chintalapani, Collate layers AI agents, automation, and enterprise support on top of an open metadata 'context layer' so data teams - and the AI models they feed - can find, understand, trust, and govern their data. The company raised a $10M Series A led by Venrock in July 2025.
Relyance AI
Relyance AI is a San Francisco-based enterprise software company that maps how data actually moves through an organization - from source code and cloud infrastructure to third-party apps and AI models - and continuously checks that movement against customer contracts, privacy regulations, and compliance frameworks. Founded in 2020 by Abhi Sharma and Leila Golchehreh, the company sells an AI-native data governance and security platform used by companies including Coinbase, Snowflake, Notion, Plaid, and Canva. It raised a $32M Series B in October 2024 led by Thomvest Ventures, bringing total funding to roughly $62-67M.
Upriver
Upriver is an AI-native data engineering platform that connects to a company's full data stack - Snowflake, Databricks, BigQuery, Airflow, dbt - then explores it, builds and validates pipelines, fixes them when they break, and encodes the tribal knowledge that usually lives in engineers' heads. Founded in 2024 by Talpiot graduates Ido Bronstein and Omri Lifshitz, the Tel Aviv company aims to make data infrastructure invisible so AI systems can run on a reliable data foundation without constant manual upkeep.
Scry AI
Scry AI is a bootstrapped enterprise artificial intelligence company founded in 2014 by Dr. Alok Aggarwal and headquartered in San Jose, California. It builds AI products that turn messy enterprise data into intelligence - intelligent document processing, anomaly and fraud detection, IoT-based predictive maintenance, conversational AI, and data lineage mapping - for finance, insurance, energy, manufacturing, and government clients. Profitable without venture funding, it reports roughly $28.4M in revenue and has appeared on the Inc. 5000 list multiple years running.
Lightup Data
Lightup Data is a Mountain View-based enterprise data observability company that lets organizations monitor data quality at scale without moving their data. Its no-code platform pushes computation down into existing warehouses and lakehouses like Snowflake and Databricks, using AI-powered anomaly detection to catch data drift, outages, and discrepancies before they reach dashboards or AI models. Founded in 2019 and backed by Andreessen Horowitz, Lightup serves enterprises including AMD, Skechers, and KFC.
Monte Carlo
Monte Carlo is the data and AI observability company that pioneered the 'data observability' category. Its platform helps enterprises detect, resolve, and prevent data and AI quality issues - what the company calls 'data downtime' - by monitoring data pipelines end to end, mapping lineage, surfacing anomalies, and tracing root causes. Founded in 2019 by Barr Moses and Lior Gavish, Monte Carlo serves 400+ enterprises including PepsiCo, Cisco, Nasdaq, and Comcast, and has raised $236M at a valuation of roughly $1.6B.
Mozart Data
Mozart Data is a San Francisco-based startup that gives companies an out-of-the-box modern data stack - a managed Snowflake warehouse, no-code ETL connectors, a SQL transformation layer, and built-in observability - so non-engineers can go from siloed, messy data to analysis-ready in about an hour. Founded in 2020 by Peter Fishman and Dan Silberman and backed by Y Combinator, it lets startups and SMBs skip the months of plumbing usually needed to stand up data infrastructure.
Striveworks
Striveworks is an Austin-based AI operations company whose Chariot platform helps organizations build, deploy, monitor, and retrain machine learning models in hours rather than months. Built for highly regulated and contested environments - especially U.S. national security and allied defense - Chariot pairs a fast MLOps workflow with end-to-end data and model lineage, giving customers governance and provenance over models that must keep working when conditions change.
Alation
Alation is a Redwood City-based enterprise software company that built one of the first modern data catalogs by pairing machine learning with human curation. Its Data Intelligence Platform helps large organizations find, trust, and govern their data, and it has since pivoted toward an agentic AI platform that uses autonomous agents to automate data discovery, governance, and quality. The company serves roughly 450 enterprise customers, including more than a quarter of the Fortune 100, and has raised about $340 million at a valuation north of $1.7 billion.
Acceldata
Acceldata is an enterprise data observability and agentic data management company that helps large organizations monitor, govern, and optimize the pipelines, warehouses, and lakes powering modern analytics and AI. Founded in 2018 by former Hortonworks engineers, it now serves customers like Oracle, Verisk, PhonePe, and Dun & Bradstreet, and recently launched an Autonomous Data & AI Platform built around its xLake Model Context Protocol for agentic workloads.
Atlan
Atlan is a data and AI control plane - a metadata-driven workspace that helps data teams catalog, govern, and collaborate across the modern data stack. Built like Figma for data, it sits between tools like Snowflake, Databricks, dbt and BI dashboards to give companies a single source of truth for what their data means, who owns it, and whether it can be trusted by humans or AI agents.
Varun Banka
Varun Banka is the Co-Founder and Co-CEO of Atlan, the active metadata platform and data governance control plane trusted by 200+ enterprise customers across 50+ countries. Originally from Ranchi, India, Varun co-founded SocialCops with Prukalpa Sankar while studying at Nanyang Technological University - a data-for-social-good company that powered India's national data platform used by PM Modi and impacted over a billion lives. When their internal data tooling made their own team 6x more agile, they realized the world's data teams needed the same. Atlan was born, raised $105M Series C in May 2024 at a $750M valuation, and is now building what it calls the 'context layer for the AI-native enterprise.'