What if your AI didn’t just respond — it reasoned? At #NVIDIAGTC, we’re showing how AI agents are evolving into a true Agentic Workforce: systems that automate, predict, and optimize across your entire business. Stop by the DataRobot booth 427 to: 🤖 View a live demo of our Agent Workforce Platform, co-developed with NVIDIA 💬 Talk to our experts about how we leverage Nemotron at DataRobot 💼 Explore use cases for industries like Federal and beyond 🎟️ Want to attend GTC? Use our link for 20% off your pass: https://bit.ly/4opTCkm
About us
DataRobot delivers the industry-leading AI applications and platform that maximize impact and minimize risk for your business.
- Website
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https://www.datarobot.com
External link for DataRobot
- Industry
- Software Development
- Company size
- 501-1,000 employees
- Headquarters
- Boston, Massachusetts
- Type
- Privately Held
- Specialties
- AI Experimentation, Generative AI, Secure, flexible deployment , End-to-end AI platform, Enterprise ready governance , Prebuilt customizable agents, Code first tooling, Accelerated time-to-value, Integrated MLOps, Agentic tracing, Explainable AI (XAI), Rapid model development, AI lifecycle management, Automated guardrails, Actionable insights, Times series analysis, Model agnostic development, Cloud agnostic deployment , Data science, and Accelerated agent development
Products
DataRobot
Data Science & Machine Learning Platforms
DataRobot delivers the industry-leading AI applications and platform that maximize impact and minimize risk for your business. Learn more at datarobot.com.
Locations
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Primary
225 Franklin St
Floor 13
Boston, Massachusetts 02110, US
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140 New Montgomery St
San Francisco, California 94105, US
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Kyiv, UA
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London, GB
Employees at DataRobot
Updates
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Scale your agent workforce with open reasoning models. You can harness Qwen3-Next’s long-text reasoning and mixture-of-experts design to power more flexible, capable agents. With these models and the DataRobot Agent Workforce Platform, you can build intelligent agent workforces that scale in any environment. Excited to see NVIDIA push open-source forward: https://bit.ly/48j3zez
The new open-source Qwen3-Next Instruct and Thinking models put state-of-the-art long-context reasoning into the hands of everyone. We collaborated with #opensource frameworks from sgl-project, and vLLM to enable communities to deploy Qwen3-Next across the full-stack NVIDIA AI platform. Built with a hybrid MoE design and CUDA-accelerated attention, these models are also available as NVIDIA NIM, ready to run anywhere. 🔗 Learn more & download: https://nvda.ws/463u9qv
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Bigger models don’t always mean better results. We tested OpenAI’s GPT-OSS 20B & 120B with our open-source optimizer, syftr. Which delivers the best mix of speed, cost, and accuracy? Full results here → https://bit.ly/4nz5IaJ
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Real-world leaders. Real-world lessons. At Agents in the AM, you’ll hear directly from CIOs and developers who are already putting AI agents to work in production. 👔 CIOs: Discover proven strategies to move beyond pilots. 💻 Developers: Test-drive the tools and techniques for building agents that actually scale. Here’s what you’ll experience: ✅ CIOs sharing firsthand production success stories ✅ Developer-tested frameworks and approaches ✅ A hands-on NVIDIA + DataRobot lab 📍 We’re kicking off in Boston on October 21. 👉 Register here: https://bit.ly/41LLkud
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Enterprises don’t need more AI tools. They need an AI gateway that actually works at scale. And unless it delivers on three non-negotiables—abstraction, control, and agility—you won’t get past the pilot stage. We break down what makes an AI gateway enterprise-ready (and what to watch out for) in our new blog. 👉 Get the framework here: https://bit.ly/3K19Gdv
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Sunday recap edition☕ From real-world impact to real-world innovation — here’s what we’ve been up to: 🌍 AI for Good — Virtue Foundation is using DataRobot to match hundreds more volunteers to high-need healthcare locations around the world, helping bring life-saving care where it’s needed most. ⚙️ Agentic AI, Anywhere — The DataRobot Agent Workforce Platform supports NVIDIA Nemotron models, bringing open, transparent, and adaptable AI to every environment — from the cloud to air-gapped systems. 🎙️ On Stage & On the Move — Our VP Hari Ashvini joined Kumo’s Joshua Przybylko at AIX Summit to discuss how AI agents act on insights. 🧠 Research Spotlight — Our team put OpenAI’s GPT-OSS models to the test with syftr, our open-source optimizer — revealing why “bigger” doesn’t always mean “better.” 🌐 Global Stage — Stephan Paul will represent DataRobot on the AI Stage at #GITEX2025, joining industry leaders to talk about scaling AI responsibly — before heading to Agents in the AM Dubai next month. 🏭 AI + SAP in Action — One manufacturing customer turned years of untapped data into real operational impact using SAP and DataRobot — a repeatable pattern for many SAP-driven organizations. Want to see what we're up to next? Join us for Agents in the AM — a pop-up event where enterprise-ready agents go from idea to reality before lunch. We’re kicking off in Boston: https://bit.ly/41LLkud
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What’s holding back AI at scale? Spoiler: it’s not the tech. At our AIX Summit, industry leaders shared lessons on how to turn agentic AI from pilots into real, scalable impact. Check out the takeaways 👇
What if the biggest barrier to scaling #AI isn't technology? What if it’s … us? At the recent DataRobot #AIXSummit, numerous AI experts shared a surprising truth: most #AgenticAI projects don’t fail because the math is wrong, or the models underperform. They fail because of how people and processes respond to them. Resistance, poor integration, and misaligned goals derail even the best tech. Industry leaders shared three practical ways to reframe, re-integrate, and re-strategize, turning agents from abstract experiments into a real workforce that scales. https://lnkd.in/gVrNME_B #FederalGovernment
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Bring the best reasoning models to where the work gets done. NVIDIA Nemotron was built with open source at its core so developers, researchers, and enterprises can build together. With the DataRobot Agent Workforce Platform, organizations can put that innovation to work in developing, delivering, and governing agentic AI with full visibility, from cloud to air-gapped environments. Learn more: https://bit.ly/3WsGA9w
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Every enterprise has years of untapped data. The real question is: how to turn it into impact?🤔 This manufacturing customer used SAP S/4HANA, SAP BW, and SCADA production data powered by SAP BDC, SAP Business AI, and DataRobot to transform operations with AI. The solution pattern is repeatable and relevant for many SAP Business Technology Platform customers facing similar challenges. Read more in our joint blog series 👇
SAP Champion | Solution Architect of SAP BTP&AI at SAP SE. Inspiring and enabling partners to build Intelligent and Sustainable Solutions with #sapbtp & #ai.
Weeks ago, during my SAP BDC Deep-dive Workshops in Sydney and Melbourne, I have shared a real-life customer story of Data&AI-driven Business Transformation by NTT DATA UK, in collaboration with SAP and DataRobot. The audience found it really interesting and inspiring with a heated discussion. Here you have the customer's use case in blog post by Mark Wheeler from NTT DATA. 🔗 https://lnkd.in/gWVpwNwr This is the first blog post of a collaborative blog post series between NTT DATA, SAP and Data Robot about an over-two-decades real-life manufacturing SAP customer's journey towards the new era of Data and AI with the help of SAP BDC, SAP Business AI and Data Robot, involving SAP S/4HANA on premise, SAP BW, and Scada Data from production lines. That said, the pattern of the use case and solution architecture is applicable to many other SAP customers from different industries with the similar challenges. It all starts with a question from the customer's executive board. “The board wants to know what meaningful impact we can get from two decades of SAP data on our business?” Quickly in action, NTT DATA team up with Data Robot to build up a PoC with custom AI models by combining production order data and quality data from SAP S/4HANA and SCADATA data from production lines to ✅ Identify the compound factors of a waste event on the production lines, reduce even eliminate the production waste. Resulting in not only financial benefit in millions of GBP, but also heading to zero waste goal in environmental sustainability. ✅ Find out the optimal setup of machinery to produce the high quality product with minimal resource. Gaining product quality improvement and production efficiency. Please stay tuned for the upcoming blog posts about each step and component of the solution architecture in details. 1.Use Case and Architecture outline (NTT Data) 2.SAP S/4HANA Production Orders, Quality Data, and SCADA Data Ingestion into SAP BDC (SAP) 3.Real-time streaming and MLOps (Data Robot) 4.Event driven interventions (NTT Data) The team behind the scene: NTT DATA(UK): Mark Wheeler, Asad Mahmood, Simon Schwarze, Tobias Maier SAP: Yatsea Li, Alice Magnani, Dr. Merza Klaghstan, Wael Labidi, Hans-Joachim Odlozinski Data Robot: Anthony Smith, Nolan KONG, Gwyn Evans
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