From FDA-regulated data flows to AI pipelines in public companies, our governance frameworks hold up under scrutiny and scale across orgs.
Lineage, RBAC, and audits are only effective if they’re adopted. We build governance systems that teams use - because they don’t slow things down.
Every policy we define is backed by tooling, automation, and integration - no hand-wavy slides or unenforced best practices.
We’ve mapped prompt libraries, grounding datasets, and model inputs with full traceability - ensuring your GenAI systems stay governed from source to output.
Yes. We assess, design, and operationalize — integrating with your stack, IAM systems, and workflows to ensure policy enforcement.
We work across Snowflake, Redshift, Databricks, BigQuery, S3, and others — using IAM, policy-as-code, tagging, and data masking where needed.
We help trace dataset usage, prompt lineage, and grounding inputs — aligning model inputs and outputs with governance rules.
Focused rollouts (lineage + RBAC) can be deployed in weeks; enterprise-wide maturity roadmaps span 6–12 weeks based on scope.
Yes. We work with Collibra, Alation, Atlan, or open-source tooling — or help you set up a lightweight governance layer from scratch.
We begin with a $0 Governance Readiness Assessment — and deliver a clear execution plan based on your stack, gaps, and priorities.
