For most teams, the hardest part of GenAI isn’t the model—it’s the last mile:
prompt tuning, chunking strategies, evaluation, and endless manual iteration.
Databricks Agent Bricks automates the busywork, so you can focus on business logic and impact.
⚡ Build a PoC in ~3-4 hours
- Declare the Task (No Framework Overhead)
Skip complex LangChain pipelines. Just describe your goal in plain English.
“Create a Financial Analyst that summarizes Q3 earnings reports.”
That’s it.
2. Connect Your Data — The Unity Catalog Way
Point Agent Bricks to PDFs, documents, or Delta tables in your Lakehouse.
Because it’s natively integrated with Unity Catalog, security and governance are automatic—your agent only sees what it’s allowed to see.
3. Auto-Evaluate & Optimize (The Real Breakthrough)
This is where Agent Bricks shines:
- Generates synthetic test data
- Uses AI Judges to score accuracy, relevance, and tone
- Runs model + prompt sweeps to balance quality vs. cost
No custom eval pipelines. No guesswork.
4. One-Click Deployment
When the metrics look good, deploy instantly as a scalable endpoint.
With Scale-to-Zero, you only pay when it’s actually used—perfect for PoCs.
Which Brick Should You Start With?
- Knowledge Assistant – RAG chatbot over enterprise docs with citations
- Information Extraction – Convert 10,000 messy PDFs into clean Delta tables
- Custom LLM – Fine-tune models for domain-specific language
- Multi-Agent Supervisor – Coordinate multiple agents for complex workflows
The Bottom Line
What used to take weeks of manual tuning can now be factory-optimized and feedback-ready in a few hours.
Have you tried Agent Bricks yet?
How are you closing the evaluation gap in your GenAI projects? Comment below:
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