DataRobot Spring 2024

Confidently Deploy and Govern GenAI Solutions

Datarobot delivers testing, optimization and AI observability to enable customers to create production-grade AI applications, observe and intervene in real-time and govern and optimize the infrastructure.

Create Production-Grade AI Applications

Build safe and useful generative and predictive applications with advanced RAG testing and evaluation techniques.

  • Enterprise-grade open source LLM support: Leverage any open source foundation models — LLaMa, Hugging Face, Falcon or Mistral, and new models like Nematron-3-8B.
  • LLM Metrics Evaluation and Assessment: Quickly evaluate the quality of your RAG pipeline with metrics like correctness, faithfulness and effectiveness along with user feedback integration and guard model testing to ensure optimal performance and safety.
  • LLM Playground Advanced Testing: Advanced production-tested RAG workflow and customization tools let you test various embedding strategies, chunking strategies, and LLMs.
  • Notebook Codespaces: Seamlessly collaborate on AI projects accessible from anywhere, version control with Git, work on multiple notebooks simultaneously, all in a user-friendly interface for efficient code development and deployment.
  • Model Training on GPUs in Workbench: Accelerate model training and improve productivity with NVIDIA Rapids GPU accelerated libraries in DataRobot notebooks.
  • Q&A Chat App: Accelerate experimentation with ready to use, interactive, GenAI application that can be shared with stakeholders to test GenAI experiments created in the DataRobot playground
  • App Workshop: Eliminate complex deployment hurdles with a release-ready AI app workshop. Centralize how users register, catalog, deploy, and manage the full life cycle without tool hopping. 
  • Prompt Tracing: Pinpoint the source of a model’s performance problem and map it back to the place in your vector database causing the issue, then leverage user feedback to train predictive models, enhancing model performance and user experience.
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Observe and Intervene in Real-Time

Quickly detect and prevent unexpected and unwanted behaviors.

  • Unified Registry for GenAI Apps and ML Models: Standardize AI visibility, deployment, integration, and monitoring for individuals or groups of machine learning models and AI applications.
  • GenAI Guard Library: Control model performance with a full suite of out-of-the-box metrics, custom guard models, and methods, including resource consumption, PII detection, toxicity, faithfulness, and more.
  • Real-time LLM Intervention and Moderation: Create a strong, multilayered defense strategy and minimize risk with dynamic real-time oversight and intervention methods at prompt and response to prevent issues like hallucinations, prompt injection, and PII leakage.
  • Multi-Language GenAI Text Drift: Assess topic trends from user interactions and leverage data drift word cloud insights to augment vector databases, adjust RAG models, or fine-tune models for text generation projects.
  • Custom Governance Tests via Jobs: Validate model performance and behaviors, and create custom explainability insights to export charts and coefficients for compliance documentation.
Configure evaluation and moderation

Govern and Optimize Infrastructure Investments

Get more value from your existing infrastructure with a purpose-built AI platform.

  • NVIDIA Inference Triton Server Integration: Seamlessly deploy high-performance models with NVIDIA’s Triton Inference Server integration, with extra acceleration on all your GPU-based models, optimizing inference speed and resource efficiency.
  • Optimized AI Inference with NVIDIA Inference Microserves (NIMs): Enhance model training and remove the need for individual GPU-powered systems with NVIDIA Inference Microservices in DataRobot.
  • Cross-Cloud & Hybrid AI Observability: Effortlessly manage your AI portfolio across cloud and hybrid environments with comprehensive observability, cross-environment visibility, and unified governance.
  • Global Models: Ensure consistent security and performance monitoring across your AI assets with Open Source Deep Learning and NLP models and share the best performing models with contributors.
  • Registry Jobs and Notification Policies: Validate model performance and behavior and reduce time-to-detection and time-to-resolution with real-time notifications and highly customizable alerting. 
  • Custom Apps Sharing: Safely share custom GenAI apps with stakeholders inside or outside your organization while adhering to governance and security policies through granular RBAC and governance policies.

Go the DataRobot Documentation Release Center for more information.