Tagged: mlops
30 results
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.
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.
Thread AI
Thread AI is a New York enterprise software company building composable infrastructure for AI-powered workflows. Founded in 2023 by former Palantir AI/ML leaders Angela McNeal and Mayada Gonimah, its flagship platform Lemma pairs a drag-and-drop workflow builder with orchestration infrastructure so organizations can connect disparate systems, data, and AI models into governed, observable, end-to-end workflows - without ripping out their existing stack. The company raised a $20M Series A in 2025 to help enterprises and public-sector agencies deploy mission-critical AI with control, traceability, and security.
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.
DataPattern
DataPattern is a San Ramon, California based IT services and consulting firm founded in 2019 that helps regulated and data-heavy enterprises move from legacy systems to modern data, AI and IoT platforms. Its teams build data engineering pipelines, generative AI and machine learning solutions, IoT use cases, cloud migrations and DevOps/MLOps practices, with a stated emphasis on data governance, quality and lineage as the foundation for reliable AI. The company works across manufacturing, healthcare, finance and energy, positioning itself as a hands-on transformation partner rather than a single-product vendor.
DataRobot
DataRobot is an enterprise AI platform company founded in 2012 that helps organizations build, deploy, govern, and monitor predictive and generative AI. A pioneer of automated machine learning (AutoML), the company has since expanded into MLOps, generative AI, and agentic AI, letting technical and business teams move models from experimentation into production with governance and observability built in. More than 1,000 organizations - including enterprises, hospitals, and government agencies - rely on its platform, now centered on an Agent Workforce Platform co-engineered with NVIDIA.
Forte Group
Forte Group is an AI-first software development and consulting firm founded in 2000 and headquartered in Boca Raton, Florida. Bootstrapped since day one, it delivers custom software, data and analytics, quality engineering, and Salesforce services through roughly 800-900 engineers across a dozen locations in the Americas and Europe. The company built its reputation on outcome-based engineering - tying its work to measurable business results rather than billable hours - and now embeds AI across the full product lifecycle for clients in finance, healthcare, logistics, retail, SaaS, and beyond.
InfoObjects Inc.
InfoObjects Inc. is a San Jose-based AI consulting and digital transformation firm, founded in 2005 by Rishi Yadav. Built originally around the open-source big data stack - Apache Spark, Kafka and Hadoop - the company has repositioned around generative and agentic AI, offering services from data engineering and cloud migration to LLM fine-tuning, retrieval-augmented generation and AI application development. It partners with AWS, Google Cloud, Microsoft Azure, Databricks, Anthropic and OpenAI, and works with enterprise clients across finance, healthcare, manufacturing and retail.
dotData
dotData is a Silicon Valley enterprise AI company that automates the most time-consuming part of data science: feature engineering. Spun out of NEC Corporation in 2018 and led by founder Ryohei Fujimaki, dotData builds software that automatically discovers signals hidden across multiple data tables and turns them into predictive features and business hypotheses. Its products - dotData Enterprise, Feature Factory, and the generative-AI-powered dotData Insight - let analysts and data scientists build models and surface KPI drivers in a fraction of the usual time, and are used heavily in financial services, insurance, manufacturing, retail, and telecom.
ModelCat AI
ModelCat AI, formerly the low-power chip pioneer Eta Compute, builds an agentic, hardware-aware platform that automatically designs, trains, optimizes and validates machine-learning models for embedded, edge and IoT devices. Its patented AI-in-the-Loop workflow, backed by a physical hardware farm that calibrates results against real silicon, compresses a model-development cycle that once took 12 to 24 months down to a matter of days. The Sunnyvale company works with chipmakers including NXP and Alif Semiconductor to hand developers ready-to-run models tuned to the exact constraints of the hardware they will run on.
Roboflow
Roboflow is a computer vision platform that gives developers and enterprises everything needed to go from raw images and video to production vision applications - dataset management, AI-assisted annotation, hosted training, low-code Workflows, and deployment to the cloud or the edge. Founded in 2019 by Joseph Nelson and Brad Dwyer, it is used by over a million developers and more than half of the Fortune 100, and maintains widely adopted open-source tools including Inference, supervision, Autodistill, and the state-of-the-art RF-DETR detection model.
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.
Vectice
Vectice is a San Francisco-based enterprise software company that builds a 'Regulatory MLOps' platform to automate the documentation, governance, and collaborative review of AI/ML models. Using a lightweight autolog library, it captures model, data, and code lineage from tools like Python, Databricks, and Snowflake, then assembles audit-ready model development and validation documents mapped to regulatory frameworks such as SR 11-7, the EU AI Act, ISO/IEC 42001, and NIST AI. Founded in 2020 and backed by $15.6M in seed and Series A funding, Vectice targets banks, insurers, and other heavily regulated enterprises that need to scale AI without drowning in compliance paperwork.
VESSL AI
VESSL AI is an MLOps and GPU-cloud company that helps AI teams train, deploy, and scale machine learning models without wrestling with infrastructure. Its platform pools GPU capacity across on-premise clusters and multiple cloud providers, automatically routing workloads to the cheapest available resources - a hybrid, multi-cloud approach the company says can cut GPU spend by up to 80%. Founded in 2020 by ex-Google and PUBG engineers and split between Seoul and the San Francisco Bay Area, VESSL serves roughly 50 enterprise customers and 2,000-plus users, and has expanded into AI-agent tooling with its open-source Hyperpocket project.
Cake
Cake is a New York-based startup that bundles the sprawling open-source AI stack into a single managed platform, so companies - especially in regulated industries like finance, insurance and healthcare - can deploy AI inside their own cloud without wiring together 100+ tools by hand. Founded in 2022 by Misha Herscu and Skyler Thomas and launched from stealth in December 2024 with a $13M seed led by Google's Gradient Ventures, Cake handles the integration, security, governance and cost-monitoring glue around open-source components like LangChain, Ray, MLflow and vector databases, all deployed inside a customer's own VPC so data never leaves.
SQOR.ai
SQOR.ai is a New York-based, AI-native decision intelligence platform that replaces legacy business-intelligence complexity with a plug-and-play system. It connects read-only to 800+ data sources and SaaS tools a company already uses, unifies their KPIs, and deploys 60+ AI agents that apply machine learning for causation, prediction, and recommendation - so operators, funds, and their LPs can ask questions in plain language and get objective answers in minutes instead of quarters. Its proprietary Execution Score Algorithm (ESA) quantifies operational health at the tool, division, and company level.
James Rebesco
James (Jim) Rebesco is the co-founder and CEO of Striveworks, an Austin-based AI company that helps the U.S. defense and national-security community build, deploy, and monitor machine-learning models at scale through its Chariot platform. A physicist by training (Caltech) and a computational neuroscientist by doctorate (Northwestern), he spent seven years as a partner at high-frequency trading firm Virtu Financial before turning to operational AI. Under his leadership Striveworks has landed a $70M enterprise government agreement, raised a Series B led by Washington Harbour Partners, and become the first company to bridge the U.S. Army's two largest battlefield AI efforts.
FriendliAI
FriendliAI is a San Francisco-based AI inference cloud built by the researchers who invented continuous batching - the technique now standard across the industry. Its platform serves open-weight and custom generative AI models in production with high throughput, lower GPU costs, and 99.99% reliability, used by customers including LG and Twelve Labs.
Openlayer
Openlayer is an AI governance and observability platform that helps enterprise teams test, monitor, and trust their machine learning and LLM systems across the full lifecycle - from prototype to production. Founded by ex-Apple, Amazon and Harvard alumni and backed by Y Combinator and Race Capital, the company raised a $14.5M Series A in May 2025.
Swarm
Swarm is an AI consulting and engineering company that assembles on-demand GenAI teams to help enterprises move from prototype to production. It addresses the high failure rate of AI projects by deploying boutique 'Hives' of specialists - covering strategy, data, modeling, MLOps, and delivery - for Fortune 100 customers across finance, healthcare, energy, legal and retail.
Misha Herscu
Misha Herscu is the co-founder and CEO of Cake, a New York based platform that bundles more than 100 open-source AI components into managed, production-ready infrastructure so mid-market teams get the control of a build with the ease of a buy. A Harvard physics graduate turned full-stack engineer, he previously founded the radiology AI marketplace EnvoyAI (McCoy Medical Technologies), which TeraRecon acquired in 2018. After running over 200 customer-discovery calls as an operator in residence at Primary Venture Partners, he started Cake in 2022 with CTO Skyler Thomas and raised a $13M seed round led by Google's Gradient in late 2024.
OnStak
OnStak is a Milpitas, California enterprise AI consulting and hybrid-cloud services firm that helps large organizations move from AI experimentation to AI in production. With a delivery team that is roughly three-quarters AI architects and engineers, OnStak modernizes data platforms, applications and infrastructure across Cisco, NVIDIA, AWS, Oracle and on-premises environments, and ships AI products like AI Correlation Fabric, AI Assurance and AI Video Analytics. Its pitch is plain: 'Fluent in strategy, native in engineering' - straight talk about what is broken and what to fix first.
Tryolabs
Tryolabs is a Montevideo-born AI and machine learning consultancy that builds custom data and AI solutions for companies worldwide. Founded in 2009, it pairs deep engineering with applied research across computer vision, NLP, generative AI and MLOps, and is known for open-source tools like Norfair and Luminoth. Its clients range from MercadoLibre and LATAM Airlines to Halliburton, Allianz and UNICEF, spanning retail, insurance, manufacturing, telecom, oil and gas and transportation.
ModelOp
ModelOp is a Chicago-based enterprise software company that builds AI governance and lifecycle automation software. Its flagship platform, ModelOp Center, acts as a centralized system of record and 'control tower' for all of an organization's AI - traditional machine learning, generative AI, agentic AI, and third-party tools - letting enterprises inventory every model, automate approvals and testing, enforce policy, monitor production systems for drift and risk, and produce audit-ready documentation. The company sells primarily to large, regulated enterprises such as financial services, healthcare, and government, and counts Fortune 500 names among its customers.
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.
Pete Foley
Pete Foley is a serial enterprise-software entrepreneur and the co-founder of ModelOp, the Chicago-based company that built one of the first platforms for governing AI models the way banks govern money. Over a 35-year career he has run and exited a string of infrastructure companies - Infoblox, PortAuthority (to Websense), RingCube (to Citrix), Graphite Systems (to EMC) - before betting that the hardest problem in artificial intelligence would not be building models but trusting them. He served as ModelOp's CEO from its founding and now supports the company from its board of directors.
Comet
Comet is an AI developer platform that helps machine learning and AI teams track, evaluate, monitor, and manage models across their full lifecycle - from training experiments to production LLM and agentic applications. Founded in 2017 by Gideon Mendels and Nimrod Lahav, the New York-based company built its reputation on experiment tracking ('GitHub for machine learning') and now extends that into the generative-AI era with Opik, its open-source LLM observability and evaluation platform.
Manifold
Manifold is a Boston-area applied-AI company building a vertical agent platform for life sciences. Its software helps pharma companies, molecular diagnostics firms, biobanks and academic medical centers turn messy multimodal biomedical data into governed, analysis-ready insight - compressing workflows that used to take months into minutes, while keeping the data governance that regulated research demands. Founded in 2016 and led by CEO Vinay Seth Mohta, the company raised an $18M Series B in December 2025, bringing total funding to roughly $40M.
Gideon Mendels
Gideon Mendels is the co-founder and CEO of Comet, the New York machine-learning platform that tracks, compares, and explains the experiments behind AI models. A computer scientist and NLP researcher by training, he built hate-speech detection at Google and ran speech-recognition research at Columbia before turning the messy, undocumented reality of model-building into a company. In 2024 Comet shipped Opik, an open-source LLM evaluation tool, putting Mendels at the center of the scramble to make AI agents reliable in production.