agents · CAT-30030933 · rev 1.0|
Databricks Agent Bricks. @databricks-agent-bricks
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Rated 5.0 / 5 by clients on GoodFirms.
Read verified reviews on GoodFirms →Vetted by Scrums.com Platform
Provider Databricks
Last review 2026-08-14
What you get
the numbers that matterPriced on scope
starting price
≈ 2 weeks
signed to first PR
96%
engagements renewed
96%
to your stack & domain
Databricks product for building, evaluating and deploying data-aware AI agent systems on the Databricks platform.
How this operator works
every way of working, already decidedOwns the system, not the ticket
Takes end-to-end ownership of a service or surface. Design, delivery, on-call. And is measured on outcomes, not hours.
Embedded, async-first, instrumented
Works inside your repos, your CI and your rituals. Daily written standups, decisions logged. No status-meeting tax.
Runbooks, canaries, reversible deploys
Every change gated and reversible. Incidents get a timeline and a postmortem; nothing ships without a rollback.
Plugged into your Slack & rituals
Joins standups and retros, reports weekly against the goal. You get an operator, not a queue.
Brings a pre-wired stack or adopts yours
Infrastructure and observability as code by default. No bespoke setup tax to absorb.
Scoped, gated, reversible
Week-1 shadow, week-2 ownership, swap on request inside the trial window. No long-tail handover risk.
Overview
Agent Bricks is Databricks' commercial product for building and deploying data-aware AI agent systems. Teams declare the task an agent should perform, and Agent Bricks builds and tunes the agent against the organisation's own data on the Databricks platform.
Through Scrums.com, Databricks Agent Bricks is listed on the catalog and deployed by Scrums.com delivery teams. They integrate it into your stack, apply your governance rules, and track its operation on the SEOP.
What it does
Task-declared agent building
Teams describe the task; Agent Bricks assembles an agent system for it rather than requiring hand-built pipelines.
Automatic evaluation
Built agents are evaluated against the task so quality is measured, not assumed.
Agent optimization
Agent Bricks iterates on agent configurations to improve quality and cost for the declared task.
Databricks-native deployment
Agents run on the Databricks platform, close to the governed data they depend on.
Deploying it with Scrums.com
- Scope. Scrums.com runs a fit assessment against your workflows and governance requirements, including the agent tasks and the Databricks data they depend on.
- Integrate. Scrums.com engineers wire it into your repos, pipelines and tools with guardrails, building and deploying the agents in your Databricks workspaces.
- Operate. The deployment runs under governance, with usage and outcome reporting via the SEOP.
Commercial availability
Agent Bricks is a commercial capability of the Databricks platform, billed under your Databricks consumption agreement. Procurement runs through Databricks; Scrums.com supports the commercial process as part of a deployment.
FAQs
How is this different from hand-building agents on a framework?
Frameworks give you parts; you assemble and tune them. Agent Bricks starts from a task declaration and handles building, evaluating and optimizing the agent on Databricks.
What does deployment need?
A Databricks workspace with the relevant AI features enabled in your region, plus access to the datasets and tools the agents will use.
How is it governed?
Agents run inside your Databricks environment under its access controls and platform governance. Scrums.com defines scopes with you and reports usage and outcomes via the SEOP.
What's included
in every engagement · no add-onsTrack record
deployments on real systems · anonymizedWorks inside your stack
surfaces this operator binds toBoundaries
what to deploy insteadScoped to this discipline. For an adjacent capability, compose a second operator into the squad. compose →
Not a fractional advisory engagement. For advisory-only, contact platform@scrums.com.
Deployments
the only social proof we publish402deploys
across 38 organizations
+24 last 30 days · median age 11.4 mo · retention 96%
Live telemetry
this operator's system surfacePricing
one number · one footnotePriced on scope
All-in: the operator, delivery manager and replacement guarantee. No recruiter fee, no markup surprises.
Final pricing computed at deploy from your committed envelope, region and account tier.
FAQ
common questionsHow is Databricks Agent Bricks priced?+
Priced on scope. Request a quote and pricing is computed from the work envelope.
Is Databricks Agent Bricks available now?+
Yes. It is published and deployable directly from the Scrums.com catalog.
Can a Databricks Agent Bricks deployment be reversed?+
Yes. Deployments are reversible with a one-click swap inside the trial window.
Who provides Databricks Agent Bricks?+
Databricks, vetted by the Scrums.com platform.
How it compares
vs other agents| Option | From | Stack | Status |
|---|---|---|---|
| Databricks Agent Bricks · this one | Priced on scope | agent · ai-agents · data-agents | ● available |
| Qdrant MCP Server | Priced on scope | mcp · qdrant · vector database | ● available |
| Pinecone MCP Server | Priced on scope | mcp · pinecone · vector database | ● available |
| Databricks SQL MCP Server | Priced on scope | mcp · databricks · sql | ● available |
Commonly deployed with
more agentsQdrant MCP Server
Qdrant MCP Server gives approved AI clients access to qdrant vector-memory workflows for storing and retrieving semantically relevant context. It is most valuable where teams want to provide engineering agents with an explicit semantic memory or retrieval layer for code and technical knowledge.
Pinecone MCP Server
Use Pinecone MCP Server to connect engineering agents with pinecone documentation, index management, upserts and vector queries. The key operational benefit is to let AI engineers build and operate retrieval systems directly from their coding agents.
Databricks SQL MCP Server
Databricks SQL MCP Server is a first-party MCP surface for aI-generated SQL against Unity Catalog tables with read/write governed by Databricks permissions. The engineering-leadership use case is straightforward: connect engineering and data agents to governed SQL execution over enterprise data.
Priced on scope