Data / IntelligenceTurn signals into evidence
Turn signals into evidence
ready for governed decisions.
We structure signals into usable intelligence. Evidence, context, and emerging patterns become material for better decisions and durable, governed agentic workflows.
A typical 9-week Data engagement, mapped.
Duration 8–10 weeks · depending on organization size
Phase 01 — Audit / Weeks 1-2
Phase 02 — Governance / Weeks 3-4
Phase 03 — Prototyping / Weeks 5-7
Phase 04 — Integration / Weeks 8-9
Client
Data access provisioning
Schema walk-throughs
Ownership confirmation
Policy alignment
Compliance review
Access decisions
Use-case selection
Pilot user pool
Eval criteria input
Rollout planning
Team training
Operational handover
QLC
Strategists
Strategists
Source inventory
lineage tracing
Quality assessment
gap classification
Governance framework
access controls drafted
Audit design
compliance mapping
Agent specification
tools, memory, evals
RAG architecture
retrieval tuned to source
Workflow integration
embedded in real tools
Adoption strategy
monitoring + handover
QLC
Agents
Agents
Auto-discovers schemas, types, distributions across sources.
Maps data flow from origin to consumption.
Detects nulls, anomalies, drift, freshness gaps.
Generates the role-permission matrix.
Drafts policy templates with regulatory alignment.
Specs the logging architecture with replay capability.
Drafts blueprints with tools, memory, evals.
Builds the RAG pipeline, hybrid semantic + lexical.
Continuous evaluation against golden datasets.
Integrates agents into existing tools and UI.
Usage telemetry and friction surfacing.
Drift detection, cost monitoring, alerting.
Deliverables
End of WK 2
PDF + Notion DB
End of WK 4
PDF / Confluence
End of WK 7
Code + Notion
End of WK 9
Code + Runbooks
Client
Data access provisioning
Schema walk-throughs
Ownership confirmation
QLC Strategists
Source inventory
lineage tracing
Quality assessment
gap classification
QLC Agents
Schema Profiler
Auto-discovers schemas, types, distributions across sources.
Crawls every connected source and produces a typed inventory — tables, columns, sample distributions, and the relationships between them — without you running a single query.
Lineage Tracer
Maps data flow from origin to consumption.
Reconstructs the lifecycle of every field: where it's produced, every transformation along the way, every place it's consumed. Surfaces upstream owners and downstream dependencies.
Quality Auditor
Detects nulls, anomalies, drift, freshness gaps.
Continuously profiles nulls, anomalies, freshness, and drift against expected distributions — flags issues before they propagate into the agent layer.
Deliverable
Data Audit + Lineage Map
End of WK 2
PDF + Notion DB
A complete inventory of source systems with typed schemas, sample distributions, and end-to-end lineage. The Notion DB is queryable; the PDF is the executive readout. Every later deliverable cites back to it.