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§ Private Profile · San Francisco, CA, USA
Open-source platform for AI developers to build, ship, and scale AI applications and machine learning models, focused on MLOps.
BentoML has raised $9.0M across 2 funding rounds.
Key people at BentoML.
BentoML has raised $9.0M in total across 2 funding rounds.
Based in San Francisco, California, BentoML provides an open-source framework and a fully managed cloud platform for serving, deploying, and scaling machine learning models. The company operates a venture-backed open-core business model, generating recurring revenue through its fully managed serverless enterprise platform, BentoCloud, while simultaneously supporting an active open-source community of over 4,000 software developers. Its infrastructure tools are currently utilized by more than 10,000 organizations globally, including over 50 Fortune 500 companies and major enterprise software clients such as Yext and Modular. Operating with an estimated workforce of 11 to 50 employees, BentoML has secured $9 million in seed funding through early investment rounds led by prominent venture capital firms DCM Ventures and Bow Capital. The machine learning infrastructure company was officially founded in 2019 by software engineers Chaoyu Yang and Shenyang Zhao.
Key people at BentoML.
BentoML has raised $9.0M across 2 funding rounds. Most recently, it raised $6.0M Seed in June 2023.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Jun 1, 2023 | $6M Seed | Hurst LIN | DCM, Granite Asia, BOW Capital | Announced |
| Nov 1, 2020 | $3M Seed | — | Acrew Capital, BOW Capital, Craft Ventures, Draper Associates, Plug & Play Ventures, Tsvc Capital, Ajay Shah | Announced |
BentoML has raised $9.0M in total across 2 funding rounds.
BentoML's investors include Hurst Lin, DCM, Granite Asia, Bow Capital, Acrew Capital, Craft Ventures, Draper Associates, Plug & Play Ventures, TSVC Capital, Ajay Shah.
BentoML is a San Francisco-based technology company that builds an open-source and cloud-based inference platform for AI developers to package, deploy, and scale machine learning models in production.[1][3][6] It serves enterprise AI teams, data scientists, and ML engineers building applications with proprietary, open-source, or fine-tuned models, solving the core problem of infrastructure complexity in model serving, inference optimization, and scalable deployment across clouds or on-premises environments.[3][4][5] The platform powers fast, secure AI apps—from RAG pipelines and agentic workflows to real-time recommendation systems—enabling organizations to compete with AI by reducing time-to-market and costs while maintaining data control.[3][4][7] BentoML has gained strong traction since its open-source launch, with thousands of AI teams adopting it, a community of over 4,000 developers, and production use at companies like TomTom and Mission Lane.[1][3][5]
BentoML was founded in 2019 by Chaoyu Yang, who drew from his experience as an early engineer at Databricks, where he encountered the challenges of scaling ML infrastructure for production workloads.[3][4] Frustrated by the complexity of deploying and serving AI models efficiently, Yang started BentoML as an open-source framework to streamline the path from prototype to production, quickly attracting thousands of AI teams and building one of the largest communities focused on model serving.[3] Key milestones include the 2023 launch of BentoCloud, a managed inference platform for custom deployments in users' clouds, and a $9M seed round led by DCM Ventures with Bow Capital participation, fueling growth amid surging demand for enterprise AI tools.[3][4] This evolution from a serving framework to a full inference platform reflects BentoML's focus on empowering ML engineers with end-to-end control.[3][5]
BentoML rides the explosive growth of generative AI and enterprise inference demands, where specialized, proprietary models on private data are shifting from proprietary APIs to customizable, secure deployments amid rising costs and compliance needs.[3][4][8] Timing is ideal post-2023 AI boom, as teams grapple with scaling LLMs beyond hype tools like LangChain, needing production-grade backends for real-time apps in recommendations, personalization, and automation.[2][4][5] Market forces like multi-cloud adoption, GPU shortages, and regulatory pressures (e.g., data locality) favor BentoML's security-first, open approach, influencing the ecosystem by democratizing inference infrastructure and accelerating AI adoption for non-hyperscalers.[3][5] It powers diverse sectors from navigation (TomTom) to fintech (Mission Lane), fostering a shift toward efficient, observable AI operations.[1][5]
BentoML is positioned to dominate enterprise AI inference as workloads explode, with expansions into advanced orchestration for agentic AI and deeper multi-modal support likely next amid 2024-2026 trends like cost-optimized fine-tuning and edge inference.[3][5][8] Evolving regulations and hybrid cloud mandates will amplify its data-control edge, potentially drawing more VC and acquisitions, while community-driven innovations sustain moats against generalist platforms.[4][5] As AI shifts from experimentation to core business infrastructure, BentoML's mission to make production AI accessible will increasingly define competitive edges for enterprises—just as it began by simplifying the path Chaoyu Yang once struggled with at Databricks.[3][4]
