
Mosaic AI Agent Framework
A suite of tools by Databricks for building, deploying, and evaluating high-quality AI agents and RAG applications.
סקירה
מקרי שימוש
Build Production RAG Applications
Develop retrieval-augmented generation apps that connect LLMs to enterprise data sources for accurate, context-aware responses.
Deploy AI Agents at Scale
Create and deploy AI agents within the Databricks ecosystem, leveraging integrated tooling for reliable production rollout.
Evaluate Agent Quality
Assess the performance and quality of AI agents and RAG pipelines using built-in evaluation tools to ensure high standards.
Iterate on LLM Workflows
Prototype, test, and refine generative AI workflows in a unified framework that streamlines the agent development lifecycle.
ביקורות
ממוצע מ-4 דירוגים.
התחבר כדי להשאיר ביקורת.
Nadia Petrova
Years in this space
I've evaluated a lot of these over the years. What stands out here is the integrations — handled better than most — and the value for money is strong. The mobile experience lags is my one real gripe. Worth the time if this is your use case.
Kwame Mensah
Solid for our team
We rolled this out across the team last quarter and it saves real time. The core workflow fits neatly into how we already work, and the integrations removed a step we used to do by hand. The mobile experience lags, which is the main caveat, but it has held up under daily use.
Mei-Ling Wong
Skeptical, then convinced
I went in skeptical — most tools in this space overpromise. It actually delivers on the integrations, and it is genuinely easy to set up caught me off guard. Pricing gets steep at scale is why this isn't a perfect score, still, I'd recommend giving it a real trial.
Tomáš Novák
Solid for our team
We rolled this out across the team last quarter and the value for money is strong. The automation fits neatly into how we already work, and the API removed a step we used to do by hand. The mobile experience lags, which is the main caveat, but it has held up under daily use.
שאלות ותשובות
עדיין אין שאלות — היה הראשון לשאול.
שאל שאלה
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