Autonomous Data-ConductorGo on autopilot for your data work
Meet the Staff-Level Data Engineer who never clocks out. Reduce your data ops to zero: it runs the detect, diagnose, fix, review and verify loop across your stack autonomously, directing the whole swarm, keeping the loop turning while you sleep, and leaving a receipt on every change.
Autonomous data operations, in real time.
Observability tells you something broke, then a human spends the night fixing it. Conductor closes that gap with proactive, autonomous resolution: the same loop a senior data engineer runs, only continuous, cross-cloud, and showing its work at every turn, across every warehouse, orchestrator and transform layer you own, directing the whole swarm.
Automate whatever data work comes to mind
Set up self-healing pipelines
Autonomous root-cause analysis
Proactive data quality improvements
Automated data insights
Personalized to each user’s job and preferences
One agent that owns the outcome, not the step.
Not a chatbot you babysit, and not fifteen agents you have to coordinate yourself. It doesn’t wait for a ticket: it finds the work and finishes it. Conductor decomposes the work, sequences the right specialists end to end, holds state across every hop, and escalates exactly one decision to you. Data problems are interconnected, a quality issue is a schema issue is a pipeline issue, and single-domain tools cannot reason across that seam. Conductor is the seam.
Owns the whole incident, not one slice of it
Reasons across quality, schema, lineage and cost
Builds and runs multi-step workflows
Escalates one decision, not a queue
Autonomy you can turn all the way up.
Brakes and gears, because a system that changes production is one you have to be able to govern. Conductor ships observe-only and you open the rope domain by domain: which agents can write, how far a change may spread, what still comes to a human. Most teams start narrow and widen it as the receipts pile up. The dial goes to fully autonomous. That’s the destination, not the exception.
Set the rope per domain, observe-only to fully autonomous
Blast-radius scoping and one-click reversal
A signed receipt on every change
Every closed loop compounds into context
Data tasks across domains are autonomously resolved,
reducing human overhead across the data platform.
Fig. 1: Autonomous resolution by task class. Share of each task class closed autonomously, escalated for approval, or handled by a human, ordered by autonomous share. Darker is more autonomous. Agents autonomously complete tasks in various data domains, from data quality to data access to cost management. Illustrative.
Given a year with Data Workers, enterprises can move their data work to highly autonomous.
- Fully autonomousClosed autonomouslyL4 · Fully autonomous
- Acts on reversible changesActed, reversible onlyL3 · Act, reversible
- Proposes, waits for approvalEscalated for approvalL2 · Propose
- Observe onlyObserved onlyL1 · Observe
- Handled by a personHandled by a humanL0 · Manual
Fig. 2: Share of agent actions by rung, over twelve months. Share of all agent actions by the autonomy rung they ran at, months 0–12 of a single enterprise deployment. Five rungs, observe-only through fully autonomous, with more tasks gradually becoming more autonomous. Illustrative.
“Data infrastructure is one of the last frontiers of AI-resistant technology.”
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© 2026 Data Workers, Inc. Our copy, documentation, research and non-open-source agent designs, orchestration patterns and evaluation methods are proprietary and are not licensed for reimplementation. The open-source core is Apache-2.0 and that licence governs it. Read the full IP and AI usage notice.