Knowledge retrieval
Not a vector search layer bolted onto a prompt.
If retrieval is already in use, the risk isn't retrieval — it's access control and correctness under real conditions. Systems fail in production not because retrieval is hard, but because access boundaries and quality measurement are treated as afterthoughts.
We design retrieval as a permission-aware system from the start — access enforced at query time, quality measured continuously, degradation surfaced before users notice it.
The common failure mode isn't bad retrieval. It's invisible retrieval.
Access control handled with post-retrieval filtering. Retrieval quality guessed rather than measured. No alerting when the system degrades. These gaps matter most in multi-tenant systems and regulated environments — exactly where retrieval systems are most valuable and most exposed.
What we build
- Ingestion pipelines with structured metadata and permission extraction at ingest time
- Chunking strategies aligned to document structure and role-relevant boundaries
- RBAC-aware retrieval integrated with identity systems — access enforced at query, not filtered after
- Evaluation harnesses with recall/precision baselines and adversarial query regression
Production properties
- Tenant and role-based access enforced at query time — zero cross-tenant document exposure
- Retrieval audit trail aligned to compliance and data access requirements
- Monitoring for recall drift and latency across tenant partitions
- Runbooks and ownership documentation delivered at handoff
What this architecture guarantees — by design.
These aren't outcome projections. They're properties of how the system is built:
- Zero cross-tenant document exposure — access is enforced at the query layer against your identity system, not filtered after retrieval where gaps can slip through
- Retrieval quality is measurable, not assumed — evaluation harnesses with recall and precision baselines mean you know when the system degrades, not just when users complain
- Latency is observable under real load — monitoring across tenant partitions surfaces p95 drift before it becomes a support issue
- Your team owns it at handoff — runbooks, ownership documentation, and regression checks in CI mean no dependency on us to keep it running
Your ROI depends on your knowledge workflows, not ours.
The business case for retrieval is driven by how much time your team spends searching for answers that should already be findable — support triage, document review, internal Q&A. The Workflow Discovery maps that time, scores your data readiness, and produces your specific Efficiency Dividend. Calculate yours →
Without this architecture
- Sensitive data exposed across tenants when access control relies on post-filtering
- Retrieval quality degrades over time without recall baselines to detect it
- No visibility into latency, drift, or failure modes at the retrieval layer
- Compliance exposure when retrieval decisions can't be audited
Find out if your knowledge workflows are ready — and where the architecture needs hardening first.
The Workflow Discovery scores your data readiness, access control maturity, and retrieval quality posture across your existing workflows. 12 questions. Results immediately.
No commitment required. Findings are confidential.