DataRobot
DataRobot is an agentic AI platform that lets enterprises build, operate, and govern production-grade AI agents across cloud, hybrid, on-premise, and air-gapped environments. The platform combines foundational and purpose-built agents with governance, observability, and open-source orchestration tools such as Covalent and syftr. Its primary users are AI leaders, AI practitioners, and data scientists in sectors including financial services, healthcare, manufacturing, and government.
- Artificial Intelligence
- AI Agents
- Enterprise Software
- Software Only
- Developer Tools
Funding
Raised to date
$930MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
across 5 rounds
+32$300M · Series G+
Announced Jul 2021 · from article date
Disclosed cumulative: $930M
Founders
Tom DeGodoy
Co-Founder
Product
Problem
Enterprises have invested in data science teams and GPU infrastructure but often struggle to move agentic AI from pilots into production. Fragmented toolchains, governance risks, and rising compute costs make it difficult to scale AI agents reliably across business processes.
Solution
DataRobot provides an agentic AI platform that helps enterprises build, operate, and govern AI agents at scale. Foundational agents can be deployed and connected to an organization's specific processes and systems, while purpose-built agents are delivered and managed by DataRobot's services team. Teams can build agents with customizable blueprints and integrations in their own development environment or in DataRobot's, and select LLMs, embeddings, and other components suited to their data. The platform runs on-premise, in hybrid setups, or across multiple clouds to reduce provider lock-in. Built-in governance, monitoring, and orchestration tools are intended to keep agents performing in production.
Target Audience
The primary users are AI leaders, AI practitioners, and data scientists within large organizations in industries such as energy, financial services, healthcare, life sciences, manufacturing, and government.
Features
- Foundational and purpose-built agents for deploying AI agents into existing enterprise processes
- Customizable agent blueprints with built-in integrations and selectable LLM and embedding components
- AI governance guardrails to address common AI risks in production
- AI observability for monitoring accuracy metrics, data drift, and predictions over time
- Deployment across cloud, hybrid, on-premise, and air-gapped environments
- Open-source Covalent for infrastructure-aware compute orchestration that routes workloads across clouds, regions, or on-prem
- Open-source syftr for programmatically finding and tuning agentic workflows