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System · Data & Analytics

Let any AI agent take governed actions in Databricks

Databricks is the lakehouse platform for data engineering, analytics, and ML. Upware lets your agents act in it safely — deterministic, policy-bounded, and fully audited, without changing the system.

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Governed by policy & RBAC Full audit trail Outbound-only on-prem bridge No rip-and-replace
The problem

Why agents stall at Databricks

Databricks is excellent at surfacing data — but reading a table and acting on it are different problems entirely. An AI agent that can query Unity Catalog, trigger jobs, and write results back to operational systems is genuinely useful. Without a governed execution layer sitting between the agent and the platform, though, you get compute costs that can't be attributed, writes that bypass catalog permissions, and zero audit trail when regulators ask who ran what query at 2 a.m. Upware learns your Databricks workflows once, encapsulates each action as a policy-bound AI skill, and replays them deterministically — so agents get real capability without touching the controls Unity Catalog was built to enforce.

Unity Catalog governance
Access is governed by catalog permissions and lineage; broad agent access undermines the controls.
Compute is costly
Jobs and queries spin up real compute; ungoverned runs are expensive and hard to attribute.
Operational write-back
Pushing model or pipeline output into operational systems needs policy and verification.
What you unlock

Actions Upware makes safe in Databricks

Run governed queries and jobs
Read tables and model outputs
Write results to approved tables
Honor catalog permissions and lineage
Log runs and access for audit
The harness

AI to learn. Deterministic to execute.

Upware learns the process once and encodes it as a mostly-deterministic workflow: system interactions replay exactly, and any LLM steps are wrapped in policy, verification, and audit — so execution stays governed and drift-proof.

O
Observe & Learn
Records the real workflow once, across every system it touches.
G
Generate
Builds the API, data flow, and logic automatically — no integration project.
E
Encapsulate
Wraps it as a governed AI skill over secure MCP or API.
R
Run
Executes deterministically — RBAC, audit, and scale built in.
FAQ

Common questions

How does Upware enforce Unity Catalog permissions when an AI agent runs a query?
Upware captures the exact API calls and credential context used by a human operator when you record the workflow — it does not re-derive permissions at runtime. When an agent triggers the action, Upware replays those scoped calls through the on-prem bridge, so the request arrives with the same catalog-level identity and lineage attribution the original operator had. RBAC rules and table-level access controls are respected by construction, not by trust.
Databricks compute can get expensive fast. How do I prevent an agent from spinning up uncontrolled jobs?
Every Databricks action in Upware is a discrete, approved skill — agents cannot compose arbitrary job runs or ad-hoc queries on their own. Each skill has defined parameters, and Upware wraps execution in policy gates so a job can only be triggered under conditions you specify in advance. Every run is logged to the audit trail with the agent identity, timestamp, and cluster attribution, which also makes chargeback accounting straightforward.
Our ML pipelines write model outputs back to operational systems. Can an AI agent do that safely?
Yes, but it requires verification steps between the pipeline output and the write-back — which Upware builds into the skill rather than leaving to the agent. You define what a valid output looks like and which target tables are approved for write. Upware's deterministic execution layer handles the write with the right credentials and logs the result, while any LLM reasoning involved in interpreting the output happens upstream, bounded by policy before any data touches a production system.

Put your agents to work in Databricks

See how Upware turns a recorded workflow into a governed action in days.

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