Why Build Agents on Databricks?
Unified Data Access — Unity Catalog + Delta tables give agents governed access to structured & unstructured assets.
Serverless Compute — Accelerate LangChain/LangGraph workloads without managing clusters.
LakeFlow + Jobs — Trigger agents from batch or streaming pipelines with built‑in retries and lineage.
Marketplace Models — Swap in DBRX, Mixtral, or proprietary LLMs via one endpoint.
PipeIQ Multi‑Agent Blueprint
Supervisor Agent
Plans tasks, routes to specialist agents, enforces guardrails, and fuses responses with provenance.
Tool Agents
Text‑to‑SQL, RAG retrieval, summarisation, or external API calls—each with its own prompt and eval harness.
Observation Layer
Telemetry, cost, latency, and hallucination metrics streamed to a Lakehouse dashboard.
How PipeIQ Helps
Architecture & Design Sprints
We map user stories to agent roles, design prompt schemas, and choose the optimal LLM & vector strategy.
Agent Orchestration Framework
Implementation in LangChain/LangGraph or Autogen, wrapped in LakeFlow Jobs for reliable execution.
Evaluation & Guardrails
Automatic tests for correctness, toxicity, bias, and cost using PipeIQ's benchmark lab.
Production Observability
Dashboards, alerting, and tracing for every agent call—integrated with Databricks Lakehouse Monitoring.
Reference Architecture
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Let's Build Your Next Agent
From POC to production—PipeIQ delivers the strategy, code, and CI/CD to make multi‑agent systems real inside Databricks.
