dataops
(15)
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.
DataBahn
DataBahn is an AI-powered, security-native data pipeline and fabric platform that helps enterprises collect, enrich, orchestrate and optimize telemetry across security, observability, application and IoT/OT systems. Its agentic products - Cruz, Reef and Phantom agents - automate data engineering work, cut noise and reduce SIEM/telemetry costs by more than 50% while preserving visibility for security and IT teams.
Sigmoid
Sigmoid is an AI-first data solutions company that helps large enterprises turn complex data into measurable business value. Founded in 2013 by three IIT Kharagpur batchmates, the firm pairs deep data engineering with data science, MLOps, generative AI and agentic AI to build and operate the pipelines, models and analytics that Fortune 500 companies in CPG, retail, financial services and life sciences rely on for faster, data-driven decisions.
Synthesized
Synthesized is a London- and New York-based enterprise software company that automates the creation of production-realistic test data. Its AI-driven platform generates, masks, and subsets data from sensitive systems so teams can validate software, database migrations, and AI agents before they reach production - all while preserving privacy and meeting regulations such as GDPR. Founded in 2020 by Cambridge machine-learning PhD Nicolai Baldin, the company counts Deutsche Bank and UBS among its customers and raised a $20M Series A in September 2025.
CLOUDSUFI
CLOUDSUFI is a Silicon Valley data-driven digital transformation company that helps enterprises turn raw, siloed information into decisions - a mission it captures in the phrase 'we make enterprise data dance.' Founded in 2019 and headquartered in San Jose, California, the firm pairs data engineering, advanced analytics, and generative AI with a Google Cloud Premier partnership to modernize data platforms, automate supply chains, and unlock data monetization for customers across manufacturing, retail, financial services, energy, and digital-native industries.
K2view
K2view is an enterprise data company founded in 2009 and headquartered in Yokneam, Israel, with US operations in Texas. Its patented Data Product Platform is built on a proprietary micro-database technology that organizes fragmented enterprise data by business entity - a customer, order, product or loan - so each entity's data lives in its own encrypted, real-time, individually managed database. The approach powers data integration, test data management, data masking, synthetic data generation and, increasingly, AI-ready data pipelines that ground large language models and AI agents. K2view serves large enterprises in telecom, banking, healthcare, insurance and retail, including AT&T, Verizon, Vodafone and BBVA, and has raised roughly $43 million in funding.
Stardust AI
Stardust AI is a San Francisco-founded, data-centric AI company that helps enterprises turn raw, messy, multimodal data into the high-quality datasets that machine-learning models actually need. Through its Rosetta auto-labeling platform, its MorningStar data engine and its COSMO dataset offerings, Stardust annotates and manages 2D/3D/4D data spanning images, video, point clouds, audio and text - with heavy expertise in autonomous driving and large language models. The company works with names like SAIC Motor, BYD, Geely, Bosch, ZF, Xiaomi and JD.com, and pitches a simple thesis for the AI era: whoever controls the data controls the model.
Superb AI
Superb AI is a computer vision AI company that builds an end-to-end MLOps and DataOps platform, letting teams label, curate, train, and deploy vision models on images, video, and 3D LiDAR data. Founded in 2018 and a Y Combinator alum, it uses AI-assisted automation to shrink the slow, manual work of preparing training data, and serves enterprise customers across autonomous driving, manufacturing, security, and public sector from offices in San Mateo and Seoul.
Switchboard Software
Switchboard Software is a San Francisco-based enterprise data platform built by the team that launched Google BigQuery. It automates the messy work of collecting, transforming, blending and validating high-volume revenue and marketing data, then publishes trustworthy datasets into cloud warehouses like BigQuery and Snowflake. Marketing, revenue and data teams at media and publishing companies use it to stand up analytics and AI projects without waiting on scarce engineering resources.
Nicolai Baldin
Nicolai Baldin is the co-founder and CEO of Synthesized, a London and New York-based DataOps and AI-powered test data automation platform he launched after a PhD in machine learning and statistics at the University of Cambridge. Synthesized generates synthetic, compliant, production-like data that enterprises use to test software, train models, and share information across regulatory boundaries. In September 2025 the company raised a $20M Series A led by Redalpine to expand into automated software testing for the age of 'vibe coding.'
Pete DeJoy
Pete DeJoy is the co-founder and interim CEO of Astronomer, the New York-based data orchestration company built on Apache Airflow. A Bowdoin-trained chemist who spent eight years scaling Astronomer's product from an early commercial offering to a platform trusted by enterprises, he stepped into the CEO seat in July 2025 after a viral concert-video scandal took out his predecessor.
Ascend.io
Ascend.io is a Palo Alto-based data engineering platform that uses AI agents to automate the building, running, and maintenance of data pipelines across Snowflake, Databricks, BigQuery and beyond. Founded in 2015 by ex-Googler and Ooyala co-founder Sean Knapp, the company replaces hand-coded ETL plumbing with a metadata-driven automation engine and DataOps Agents that can write code, fix incidents and tune performance on their own.
Unravel Data
Unravel Data is a Mountain View, California company building an AI-native data observability and optimization platform. It plugs into modern data stacks - Databricks, Snowflake, Google BigQuery and Cloudera - and uses AI, machine learning and a context graph of workloads, infrastructure and users to automatically troubleshoot, tune and control the cost of data pipelines. Where most monitoring tools stop at telling teams what is wrong, Unravel aims to fix it: its newest engine, Arvix AI, rewrites code, reconfigures infrastructure and validates the changes before deploying them, so data engineers can build instead of firefight.
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.'
Sean Knapp
Sean Knapp is the founder and CEO of Ascend.io, an AI-native data engineering platform that unifies ingestion, transformation, orchestration, and observability into a single product. A Stanford-trained computer scientist, he previously built iGoogle at Google and co-founded Ooyala — a video platform that raised $120M and sold for $400M+. At Ascend, he is building what he calls 'Agentic Data Engineering,' where AI agents handle the operational burden that buries data teams, freeing engineers for strategic work.