DataRobot
by DataRobot
The AutoML pioneer turned governed agent workforce platform, co-engineered with NVIDIA.
DataRobot is an enterprise AI platform that lets data science and IT teams build, deploy, monitor and govern predictive models, generative AI applications and AI agents in one place. Co-engineered with NVIDIA, it targets large regulated enterprises that need agents in production across cloud, on-premise or air-gapped environments.
DataRobot is an enterprise AI platform vendor founded in 2012 and headquartered in Boston that built its reputation on automated machine learning (AutoML) and MLOps for predictive models, and has since repositioned itself as an "agent workforce platform" for building, operating and governing AI agents in production. The Agent Workforce Platform, announced on July 31, 2025 and co-engineered with NVIDIA, bundles agent templates for CrewAI, LangGraph and LlamaIndex, built-in evaluation and policy controls, distributed tracing across agent and tool execution, agent identity and user delegation, autoscaling and real-time monitoring, and integrates NVIDIA AI Enterprise, including more than 70 NIM and NeMo microservices and NVIDIA AI Blueprints. The predictive heritage remains in the product: the 30-day trial unlocks the agent builder, AutoML and a GenAI workbench together. DataRobot acquired Agnostiq and its open-source Covalent compute-orchestration framework in February 2025 and open-sourced the syftr workflow optimizer in May 2025. In 2026 it announced validated AI-factory stacks with Dell (March 17) and Nebius (March 18), agentic autonomous-inspection work with Chevron (June 2), and on July 22 extended the platform to on-premise, air-gapped, virtual private cloud and hybrid deployments under unified governance, aimed at sovereign-AI buyers in financial services, defense and healthcare. Gartner named it a Leader in the Magic Quadrant for Data Science and Machine Learning Platforms for a third consecutive year in June 2026. The company has raised about $1.1 billion, most recently a $300 million Series G in July 2021 at a $6.3 billion valuation, though Sacra reports investor fund marks since late 2025 implying steep valuation compression. List pricing is not published.
A CIO or head of AI at a large regulated enterprise (financial services, energy, government, healthcare) that already runs predictive ML and must move AI agents into production on its own infrastructure with governance intact.
One governed platform covering AutoML models, generative AI apps and agents, deployable in the cloud, on-premise or air-gapped, instead of stitching together separate MLOps, LLMOps and agent tooling.
At a Glance
- Category
- AI Agents & Orchestration
- Pricing
- Contact for pricing
- Target Market
- CIOs, CTOs, Chief Data Officers, Data Scientists, Enterprise Developers, IT Operations
- Deployment
- Hybrid, Multi-cloud, Self-hosted
- Founded
- 2012
- Headquarters
- Boston, United States
- Customers
- 1,000+ organizations (as of 2024, per Sacra)
Key Features
- ✓Agent Workforce Platform
End-to-end build, operate and govern layer for AI agents, with templates for CrewAI, LangGraph and LlamaIndex, agent identity, user delegation and autoscaling, so agents are managed like production services rather than pilots.
- ✓Evaluation, tracing and policy controls
Built-in evaluation tools, policy controls and distributed traceability across agent and tool execution, plus local OpenTelemetry tracing in the DataRobot CLI, so failures are caught before and after deployment.
- ✓NVIDIA AI Enterprise integration
Embeds more than 70 NVIDIA NIM and NeMo microservices, NVIDIA AI Blueprints, Triton, TensorRT and MIG support, letting enterprises run validated models on their own NVIDIA GPUs.
- ✓AutoML and predictive AI
Automated feature engineering, model building and comparison for predictive use cases; reviewers report cutting model development time from months to weeks.
- ✓MLOps monitoring and drift detection
Built-in monitoring and drift detection for deployed models, giving governance and risk teams a single view of model health across the portfolio.
- ✓Deploy-anywhere options
Managed SaaS, single-tenant SaaS on AWS, Azure and GCP with region choice, self-managed, on-premise, air-gapped and hybrid deployments, backed by the acquired Covalent orchestration framework.
- ✓syftr open-source optimizer
Open-source agent optimizer that searches agentic and non-agentic RAG workflow configurations to find the best balance of accuracy, latency and cost.
Capabilities
Use Cases
- •Autonomous industrial inspections at the edge
Chevron and DataRobot announced in June 2026 agentic AI that assesses conditions in real time for robotic inspections, replacing manual approval of each mission.
- •Sovereign AI in regulated industries
Banks, defense agencies and healthcare providers deploy agents in air-gapped or on-premise environments while keeping unified governance, avoiding public-cloud data exposure.
- •Predictive modeling at scale
Analytics teams automate model building and deployment for forecasting and risk use cases; one PeerSpot reviewer reported roughly $2 million in annual savings from automation.
- •Agentic client onboarding
Aon and DataRobot announced a collaboration in January 2026 to apply agentic AI to client onboarding workflows in insurance and risk services.
- •SAP finance and supply-chain AI
SAP customers add DataRobot AI application suites for finance and supply-chain operations, distributed as an SAP Endorsed App on the SAP Store since August 2025.
Ideal For
Best For
- ✓Regulated enterprises that must run AI agents on-premise, air-gapped or in a virtual private cloud under one governance layer
- ✓Organizations with an existing predictive/AutoML model portfolio that want the same platform to govern generative and agentic workloads
- ✓Enterprises standardizing on NVIDIA AI Enterprise or an AI-factory stack from Dell or Nebius
- ✓SAP-centric companies wanting an SAP Endorsed App for finance and supply-chain AI
- ✓Data-savvy analyst teams that lack deep manual modeling expertise and need AutoML to reach production
Not Ideal For
- ✗Startups and small teams: pricing is unpublished and PeerSpot reviewers put enterprise licensing at roughly $100,000 per year, with at least one reviewer dropping the plan over cost
- ✗Teams working with very large datasets that need full visibility into model internals: reviewers report the platform lags on larger datasets and offers limited transparency into processing logic
- ✗Engineering teams that only need a lightweight open-source agent framework such as LangGraph or CrewAI and have no requirement for an enterprise governance and deployment layer
Integrations
Deployment
Market & Ratings
1,000+ organizations (as of 2024, per Sacra)
Market Analysis
Pros
- ✓Mature AutoML and MLOps; reviewers report model development shrinking from months to weeks and productivity equal to several Python/AI experts
- ✓Unusually broad deployment choice: managed or single-tenant SaaS, self-managed, on-premise, air-gapped and hybrid
- ✓Strong enterprise security posture: SOC 2 Type II, ISO 27001, HIPAA-compliant single-tenant SaaS and SAML SSO
- ✓Deep NVIDIA, Dell, Nebius and SAP partnerships reduce integration work for enterprises on those stacks
Cons
- ✗Expensive and opaque: no published pricing, and PeerSpot reviewers cite roughly $100,000 per year for enterprise licensing
- ✗Reviewers say it performs well on smaller datasets but can lag on larger ones, and offers limited transparency into model processing logic
- ✗Reviewers request stronger ETL capabilities and better third-party tool integration
- ✗Corporate stability questions: a widely discussed 2022 insider stock-sale controversy and CEO departure, and Sacra-reported fund marks valuing stakes far below the 2021 $6.3B round
- ✗Independent reviews mostly cover the AutoML product; little practitioner feedback yet exists on the agent platform launched in July 2025
Pricing
30-day free trial
$0
- ✓Full platform access: agent builder, AutoML and GenAI workbench
- ✓Choice of LLMs
- ✓Low-code or code-first
- ✓App templates gallery
- ✓Community support
- ✓No contract or commitment
Enterprise
Contact for pricing
- ✓Managed SaaS, single-tenant SaaS on AWS/Azure/GCP, or self-managed
- ✓On-premise, air-gapped and hybrid deployment
- ✓SAML SSO and MFA
- ✓HIPAA-compliant single-tenant SaaS option
DataRobot publishes no list pricing; its pricing page offers only a 30-day no-commitment trial and a demo request. PeerSpot reviewers put enterprise licensing at roughly $100,000 per year and name cost as the main complaint, with one team dropping the plan over price. Metering and deployment terms are negotiated per contract.
Security & Compliance
Connect
Sources
This page was written from 15 sources, 6 on domains other than datarobot.com.
- 1.datarobot.com — datarobot.comvendor
- 2.datarobot.com — trustcentervendor
- 3.datarobot.com — trialvendor
- 4.datarobot.com — about usvendor
- 5.datarobot.com — pressvendor
- 6.datarobot.com — datarobot announces agent workforce platform built with nvidvendor
- 7.datarobot.com — datarobot gives enterprises full control over where and how vendor
- 8.datarobot.com — a 3x leader for the agentic era datarobot named a leader agavendor
- 9.datarobot.com — datarobot and chevron collaborate to advance agentic ai for vendor
- 10.peerspot.com — datarobot reviews
- 11.sacra.com — datarobot
- 12.nebius.com — datarobot validated ai factory stack
- 13.enterpriseaiworld.com — DataRobot and NVIDIA Create Agent Workforce Platform 170777
- 14.thequantuminsider.com — datarobots acquisition of agnostiq signals a shift from quan
- 15.github.com — datarobot
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