Companies · AI / ML
San Francisco · CA, USA · AI / ML · founded 2020 · https://www.mindsdb.com/
Diligence memoA one-page analyst read on MindsDB — recommendation, valuation, rhythm, risks.→MindsDB: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
MindsDB is one of 2067 AI / ML companies tracked from San Francisco, CA, USA, on record since 2020. By capital raised it ranks mid-pack (ahead of 62% of sector peers), and mid-pack by modeled valuation est..
Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.
AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%
operates a technology-led product inferred from public copy
Grounded in: “You are a venture analyst”
Connect, Unify, Respond to any data, anywhere with human-level…
MindsDB is a fast-growing AI startup headquartered in San Francisco, California. As a leading innovator bringing AI and Data together, our passion is empowering companies to easily build AI capabilities that can Think, Understand and Orchestrate: enabling teams to move from prototyping & experimentation to production in a fast & scalable way. MindsDB was founded in 2017 by Adam Carrigan and Jorge Torres, inspired by Ian M. Banks's Culture series, in which super AI systems called Minds collaborate with other forms of life to accomplish incredible goals. Starting as an Open-Source project, MindsDB has grown to be one of the most widely used AI-Data platforms in the world, with a growing community and more than 700 contributor developers from every corner of the globe. We are backed with over $55M in funding from Mayfield, Benchmark, YCombinator, and nVidia. MindsDB is also recognized by Forbes as one of America's most promising AI companies (2021) and by Gartner as a Cool Vendor for Data and AI (2022).
As reported in public records reported — not modeled.
Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.
No round amounts on record to chart.
No staged rounds to sequence.
Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.
Not enough modeled valuation points to chart a trajectory.
Benchmarked against 2067 companies in AI / ML. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.
Raised more than 62% of sector peers (real $). Modeled value above 62% of peers (estimate).
Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| No rounds recorded. | |||||
Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.
MindsDB is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.
Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| Accord | AI / ML | — | — | — | same sector |
| Acely | AI / ML | — | — | — | same sector |
| Aedilic | AI / ML | — | — | — | same sector |
| Aemon | AI / ML | — | — | — | same sector |
| Affogato AI | AI / ML | — | — | — | same sector |
| Aftercare | AI / ML | — | — | — | same sector |
| Agentic Labs | AI / ML | — | — | — | same sector |
| Ai Aiba | AI / ML | — | — | — | same sector |
Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Mindbase Build AI influencers that autonomously create content, engage fans… | Gaming | — | — | 77% |
| Databricks, Inc. Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data Intelligence Platform. | AI / ML | Growth/Late | $41.5B | 77% |
| HelixDB The fastest & most scalable graph-vector database on the market | AI / ML | — | — | 77% |
| QuestDB High-performance time series database | Crypto / Web3 | — | — | 76% |
| LanceDB Open-source, serverless vectordb for production-scale generative AI | AI / ML | — | — | 75% |
| Clidey Turn scattered data into one platform for decision-making | SaaS / Software | — | — | 75% |
| Wordware AI agents you can rely on | AI / ML | — | — | 75% |
| Dataland AI agents for customer support. | AI / ML | — | — | 74% |
See where MindsDB sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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