▸ Engagement 03 · 4–10 weeks · From $50k

Data, Product & Security Systems

The infrastructure that makes AI features safe, fast, and trustworthy. Pipelines that feed the model, security that doesn't block velocity, product surfaces engineered for trust.

▸ What's in scope

Three pillars, one engagement

Data pipelines

ETL/ELT, CDC, vector index freshness, contract testing on schemas. The data your AI consumes has to be right and fresh — not "we re-index when someone notices."

DevSecOps

Secrets via OIDC and KMS, SAST/DAST in CI, supply-chain attestation (SLSA), dependency policy. Velocity-preserving — security gates that don't grind releases to a halt.

Product trust surfaces

Confidence indicators, source citations, fallback UX when the model errors. The frontend pieces that turn an AI feature into one users actually trust.

▸ Specialized add-ons

For teams with regulated data

Private inference path

vLLM in your VPC for sensitive workloads. Hybrid routing — sensitive prompts stay private, non-sensitive use frontier vendors via private link.

Per-prompt audit log

Every model call logged with redacted payload, requester identity, model version, and cost. Auditor-ready by design, not by retrofit.

Redaction gateway

Pre-call PII detection and removal. Patterns tuned to your data shape. Fail-closed when uncertain.

DPA & compliance support

We help shape vendor DPAs for HIPAA / GDPR / SOC 2 contexts. We're not lawyers; we know which questions to bring to yours.