Incident evidence packets
A durable, human-readable record of signals, logs, lineage, affected assets, prior incidents, hypotheses, and validation results.
Autonomous data operations
Let data platforms resolve routine failures without surrendering production control.
Revenir designs bounded autonomous data operations: systems that collect incident evidence, diagnose failures, propose or execute approved playbooks, validate the result, and preserve an auditable record.
The engineering problem
The hard part is not giving an agent tools. It is deciding when the agent has earned the right to use them.
Data observability can identify a broken pipeline, and coding agents can propose a patch. Neither capability alone establishes that the diagnosis is correct, the action is authorized, the blast radius is acceptable, or the production result is safe.
Revenir builds the control system around the agent: structured incident evidence, explicit risk tiers, deterministic playbooks, approval boundaries, isolated validation, rollback behavior, and an audit trail that records what changed and why.
Capabilities
A complete delivery system around the technical work.
Context and dependency models
Schemas, lineage, ownership, contracts, run history, runbooks, and business meaning assembled for diagnosis and impact analysis.
Risk and authorization policy
Action tiers based on blast radius, reversibility, data sensitivity, confidence, and the agent's validated track record.
Bounded remediation
Deterministic playbooks first, with agents restricted to named tools, scoped credentials, preconditions, and explicit off-limits actions.
Verification and rollback
Post-action checks, reconciliation, canaries, replay or sandbox validation, and defined rollback or escalation paths.
Evaluation and audit
Reproducible incident scenarios, action receipts, outcome scoring, and evidence for promoting or revoking autonomous authority.
Delivery model
Architecture stays connected to implementation.
Observe
Instrument the platform and define the evidence required to explain an incident.
Constrain
Classify actions by risk and encode what may be proposed, approved, executed, or never attempted.
Exercise
Replay representative failures in an isolated environment and evaluate diagnosis, action, and verification.
Earn autonomy
Start in recommendation mode and expand authority only for repeatable, low-risk actions with proven outcomes.
What the engagement creates
- Faster diagnosis grounded in inspectable production evidence
- Routine remediation constrained by explicit policy
- Human approval focused on consequential changes
- Validation and rollback attached to every executed action
- An auditable operating record that improves future response
Start with the production constraint
Bring the system that needs to change.
We will define the real engineering boundary and determine whether Revenir is the right delivery fit.
Schedule a consultation →