Design partner preview
AI-native data observability

Stateful Observability.
Provable Data Trust.

VitiOps turns failures into reasoning, your checks into knowledge, and every platform into one graph. Early, and open.

Designed to span AWS GlueAthenaDatabricks SnowflakeBigQuery PostgresKafkadbt AirflowDagster
The status quo

Today's observability stops at the symptom.

Static RCA playbooks

Predefined lineage path, cannot detect unanticipated failures.

Manually authored checks

Manual checks accumulate as tech debt, leading to false alerts.

Single-platform tooling

Cross-platform data flows remain poorly understood and unmonitored.

What's different

Three principles, built into the core.

01 / DYNAMIC RCA

Reasoning the Root Cause.

  • Catch novel, cross-signal failures fixed playbooks can't
  • Move from "these spiked together" to "this caused that"
  • Aim to cut time to root cause from days to minutes
02 / ADAPTIVE CHECKS

Automated checks, no manual authoring.

  • Baselines adapt to real-world variation, killing false alarms
  • Keys, nulls & reconciliations stay hard assertions
03 / EVERY PLATFORM

One lineage graph across the stack.

  • Reason across tools instead of forcing one platform
  • Trace any number from a board slide to source
  • Connector breadth as the moat, not an afterthought
The architecture

AI-assisted reasoning. Hard guarantees where they matter.

Layer 1 · Measure

Deterministic assertions

Keys, nulls, reconciliations. 100% precision, near-zero cost, auditable.

Layer 2 · Detect

Statistical baselines

Seasonality-aware detection that scales across millions of tables, no hand-tuning.

Layer 3 · Reason

Agentic intelligence

Agents for triage, root cause, and authoring — for confirmed incidents, never the measurement.

The model never decides whether a number is wrong.
It decides what to do about it.

Detection stays cheap and reproducible. Expensive reasoning runs only where judgment pays off.

Building trust

Autonomy, earned in stages.

Trust is the real adoption curve. Every action lives in one of three modes — and the bounds widen only as the product proves itself.

Observe Recommend Act
01
Shadow
Watches, never touches
Semantic · lineage · quality
02
Advisory
Suggests, human decides
Human approves
03
Controlled
Autonomy
Acts, within guardrails
Within bounds

shadow advisory controlled autonomy

Reliability you can prove.

I'm reaching out as a…

✓ Thanks — we'll reach out about partnering.