DataRobot
Enterprise AI / ML platform — the original automated machine-learning category-creator now repositioned around generative AI and agent applications for regulated industries and the US federal government. Once valued at $6.3B at its 2021 Series G peak; subsequently went through repeated workforce reductions and reported secondary valuation marks at a small fraction of peak. Debanjan Saha CEO since September 2022 leading the Federal AI Suite pivot.
The Business
DataRobot is a privately held enterprise AI / machine-learning platform company founded in 2012 in Boston by Jeremy Achin and Tom de Godoy. The product line spans the original automated machine-learning platform that defined the AutoML category in the 2015–2021 era, alongside the more recent generative-AI feature set including agents, custom applications and the May 2025 Federal AI Suite targeted at U.S. federal-government agencies. The company is private — it has raised approximately $1.0B+ of cumulative external capital through the July 2021 $300M Series G at a $6.3B post-money valuation led by Altimeter Capital and Tiger Global — with Debanjan Saha as CEO since September 2022 following Jeremy Achin and Dan Wright in the founder-CEO and successor-CEO roles. The 2021 Series G remains the canonical peak-valuation reference; subsequent secondary-market and tender-offer marks have been reported substantially lower in named-press coverage as the company has executed workforce reductions and a strategic pivot toward federal-government and regulated-industry verticals.
Customers and Distribution
DataRobot does not file public financials. The principal published commercial signals are the 850-customer installed base disclosed across named-press and marketing channels, the May 2025 Federal AI Suite launch with agency-specific custom applications, and the February 2025 AWS Marketplace for the U.S. Intelligence Community listing. Distribution sits across three channels: the historical direct-enterprise sales motion targeting financial services, healthcare and insurance verticals; the federal-government and U.S. Intelligence Community channel anchored on the Federal AI Suite and the AWS Marketplace listing; and the partner-and-marketplace channel including the AWS, Microsoft, Google Cloud and McKinsey relationships. Named customer disclosures are sparse relative to the 850-account installed-base claim; we decline-to-publish precise federal-agency customer counts pending primary-source disclosure.
Model Strategy
DataRobot is a Verticals-first play under the IM Framework eight-trajectories taxonomy applied to enterprise AI infrastructure: the strategic bet is that depth on automated machine learning + observability + governance + generative-AI feature line for regulated industries beats horizontal generalist AI infrastructure plays at the federal-government and Fortune 500 tier. The May 2025 Federal AI Suite launch and the February 2025 AWS Intelligence Community Marketplace listing are the canonical expressions of that vertical positioning. DataRobot is foundation-model agnostic: the platform supports the OpenAI, Anthropic, Google and open-source model surfaces through an abstraction layer rather than building a frontier model itself. The D4a supplier-diversity sub-rubric was held at 6 in the v1.6ep evidence pass on that basis. The portability profile is the defining structural variable — DataRobot’s automated-ML category-creator position has been substantially compressed by Databricks, Snowflake Cortex and the hyperscaler first-party ML platforms; the generative-AI feature line is the principal lever for net-new ARR conversion against that compression.
At A Glance
The Numbers
Headcount (FTE)
Funding to date
Leadership Team
DataRobot has experienced significant senior-leadership turnover through the 2022–2026 period including the CEO transition from Jeremy Achin to Dan Wright to Debanjan Saha. The company’s restructuring posture has driven repeated workforce reductions documented in named-press and a strategic pivot toward federal-government and regulated-industry verticals. CFO and CRO appointments are not separately public at the senior level; the careers page is the canonical entry point for senior hires.
IM Framework Scoring
IM’s structured assessment of DataRobot’s competitive position. The summary below is the headline; expand “Show the full analyst-grade analysis” near the bottom for the per-dimension reasoning and evidence. Methodology →
Funding History
| Date | Round | Raised | Post-money | Lead investor(s) |
|---|---|---|---|---|
| Jul 2021 | Series G | $300M | $6.3B | Altimeter Capital, Tiger Global (with Counterpoint Global, Franklin Templeton, ServiceNow Ventures, Sutter Hill Ventures) |
| Nov 2020 | Series F extension | $270M | $2.8B | Altimeter Capital |
| Sep 2019 | Series E | $206M | $1B | Sapphire Ventures, Tiger Global |
| 2018 | Series D | $100M | $520M | Meritech Capital |
| 2017 | Series C | $67.7M | — | NEA |
| 2016 | Series B | $33M | — | NEA |
| 2013-2014 | Seed & Series A | ~$24M cumulative | — | NEA, Atlas Venture, IA Ventures (Seed: $3.3M; Series A: $21M) |
Cumulative external capital of approximately $1.0B+ through the July 2021 $300M Series G at $6.3B post-money led by Altimeter Capital and Tiger Global. Pre-Series-G rounds included Sapphire Ventures, Meritech, NEA, Sutter Hill Ventures and Intel Capital. The 2021 Series G is the canonical peak-valuation reference point. Subsequent secondary-market and tender-offer marks have been reported at substantially lower levels in named-press coverage; DataRobot does not publicly disclose post-2021 primary-round pricing. We decline-to-publish a precise current valuation pending a primary-source disclosure.
Competitive Landscape
| Competitor | Positioning | Distribution edge | Threat profile |
|---|---|---|---|
| Databricks | Lakehouse-anchored data + AI platform — Mosaic AI for model training and serving, Genie / Agent Bricks for the agentic layer, all on top of Unity Catalog. Positions enterprise AI as a data-platform extension rather than a separate MLOps suite. | Direct enterprise sales plus the AWS, Azure and GCP marketplace channels; embedded inside Fortune 500 data-engineering procurement through the lakehouse footprint. | High — the structurally larger ML / data-platform competitor with materially higher ARR, an MLflow + Mosaic AI generative-AI stack, and the lakehouse distribution motion; the principal head-to-head on enterprise ML platform procurement. |
| Snowflake Cortex ((Snowflake)) |
AI inside the Snowflake Data Cloud — Cortex Analyst, Cortex Search and Cortex Agents; positions model serving and agents as native SQL-callable functions on top of governed warehouse data. | Bundled into existing Snowflake credit consumption; sold through Snowflake account teams across the existing data-warehouse install base — no separate procurement motion required. | High — Snowflake’s data-platform-embedded ML and generative-AI layer; bundled with the data-cloud distribution channel into the same enterprise buyer set. |
| AWS SageMaker / Azure ML / Google Vertex AI ((Hyperscalers)) |
Hyperscaler-native ML platforms positioned as the default build-it-yourself MLOps stack tightly coupled to each cloud’s compute, storage and identity layers. | Sold as a line item inside the hyperscaler enterprise agreement; consumed against committed cloud spend with zero additional procurement step for existing AWS / Azure / GCP customers. | High — first-party ML platforms from the three hyperscalers with native distribution to every enterprise cloud customer; the structural commodity-floor on enterprise ML platform pricing. |
| Hugging Face | Open-source model hub and inference platform — the canonical distribution point for transformers and the open-weights cohort; positions itself as the community-led counterweight to closed enterprise MLOps suites. | huggingface.co as the default model-discovery surface for developers; Hugging Face Enterprise Hub and Inference Endpoints sold direct to enterprises, plus partnerships with AWS Bedrock, Azure ML and Google Cloud. | Medium-High — open-source model hub and MLOps-adjacent platform; flanking risk on the generative-AI-native infrastructure surface that has become the dominant lane post-2022. |
| Anyscale / Together AI / Baseten | Open-source-stack inference and training platforms — Anyscale on Ray, Together on the open-weights coding and reasoning cohort, Baseten on developer-friendly model deployment; narrower than a full MLOps suite but faster on the GenAI surface. | Self-serve developer sign-up plus enterprise sales into AI-native teams; channel partnerships with NVIDIA, the hyperscalers and the open-weights model labs. | Medium — the generative-AI-native infrastructure cohort; competing on inference, fine-tuning and agent-orchestration surfaces rather than DataRobot’s AutoML heritage. |
Potential Risks
Valuation reset from 2021 peak — ongoing financial repositioning
DataRobot reached a $6.3B post-money valuation at the July 2021 Series G; subsequent secondary-market and tender-offer marks have been reported at substantially lower levels in named-press coverage. The company has not publicly disclosed a primary-round pricing event since 2021. The valuation reset is the dominant structural variable on the score and the principal context for understanding the Federal AI Suite pivot and the workforce-reduction posture.
Workforce reductions and senior-leadership turnover
DataRobot has experienced multiple rounds of workforce reductions documented in named-press through the 2022–2026 period, alongside repeated CEO turnover (Jeremy Achin to Dan Wright to Debanjan Saha). The current operational frame is restructuring-and-repositioning rather than growth-stage scaling. The D4e key-person dependency sub-rubric was held at 4 in the v1.6ep evidence pass reflecting the executive-bench-depth question.
Competitive substitution — Databricks, Snowflake, hyperscaler ML platforms
DataRobot’s AutoML category-creator position has been substantially compressed by Databricks (materially larger ARR, MLflow + Mosaic AI generative-AI stack, lakehouse distribution), Snowflake Cortex (data-cloud-embedded ML and generative-AI), and the hyperscaler first-party ML platforms (AWS SageMaker, Azure ML, Google Vertex AI). The substitution risk is the principal structural dynamic on the score.
Generative-AI repositioning execution risk
DataRobot has launched a generative-AI feature line and the Federal AI Suite (May 2025) positioned around agents and custom applications. The execution risk is whether the new product line converts to net-new ARR at the federal-government and regulated-industry tier rather than functioning primarily as a retention lever for the installed customer base. The watched variable is the cadence of Federal AI Suite customer disclosures.
Capital position and runway
The 2021 Series G provided multi-year runway at peak-valuation pricing; the subsequent workforce reductions imply active cost-management to extend runway against the valuation reset. Future capital events (primary round, debt facility, strategic transaction or IPO at reset valuation) are the watched variables on the funding-position frame. We decline-to-publish a precise post-2021 valuation or runway figure pending primary-source disclosure.
Recent IM Coverage
- AI Infrastructure — sector landing May 2026.
- AI Tracker — live company sourcing methodology May 2026.
Show recent press coverage of DataRobot
- May 2025 — DataRobot Launches New Federal AI Application Suite to Unlock Efficiency and Impact (DataRobot Newsroom)
- Feb 2025 — DataRobot Listed in AWS Marketplace for the U.S. Intelligence Community (DataRobot Newsroom)
- Feb 2026 — Our Path Forward — restructuring and workforce reduction announcement (DataRobot Blog)
- 2023 — Troubled AI vendor DataRobot hit by more layoffs (TechTarget)
- Sep 2022 — Debanjan Saha Named Chief Executive Officer of DataRobot (DataRobot Newsroom)
- May 2025 — DataRobot Launches Federal AI Suite (insideHPC)
Show the source register for the figures on this page
IM operates a primary-source-where-possible discipline. The figures above come from:
- Revenue: DataRobot is privately held and does not file public revenue figures. Named-press triangulation places 2024 revenue at approximately $285M (up from $226M in 2023). We decline-to-publish a precise 2025 revenue figure pending a primary-source disclosure from DataRobot’s blog or newsroom. The Federal AI Suite launch is the May 2025 anchor for the federal-government revenue trajectory.
- Customer accounts: DataRobot has named approximately 850 customers across the installed base per named-press coverage and the company’s marketing disclosures. The May 2025 Federal AI Suite launch and the February 2025 AWS Intelligence Community Marketplace listing are the canonical anchors for the federal-government vertical expansion; agency-specific customer counts are not separately published.
- Headcount: DataRobot employs approximately 835–850 people as of early 2026 per named-press triangulation, down from approximately 969 in 2024 following multiple rounds of workforce reductions documented in TechTarget and Glassdoor coverage. The company does not publicly disclose precise headcount; the careers page is the canonical entry point for hiring posture.
- Funding to date: Cumulative external capital of approximately $1.0B+ through the July 2021 $300M Series G at $6.3B post-money led by Altimeter Capital and Tiger Global. Pre-Series-G investors include Sapphire Ventures, Meritech, NEA, Sutter Hill Ventures and Intel Capital. Subsequent secondary-market marks have been reported at substantially lower levels in named-press; we decline-to-publish a precise current valuation.
Methodology & Disclaimer
For metric definitions, source-tier hierarchy, and decline-to-publish rules, see the tracker methodology. Confidence dots (• green / • amber / • red) follow the same convention as the AI Tracker.
Spotted a figure you believe is wrong? Send corrections to info@informationmatters.net.
Information Matters Framework scores are the considered opinion of the IM team — human and AI — applied to publicly-available evidence under a disclosed methodology. They are not statements of fact about the companies scored and they are not investment advice.
