Documentation
Implementation Frameworks
Technical guides and strategic blueprints for shipping AI that drives enterprise value.
Quick Links
AI Governance Framework
Shipping AI at scale requires a balance of speed and safety. Our governance framework covers:
- Data Privacy: Ensuring no PII or sensitive business IP is used for model training.
- Risk Assessment: Categorizing AI use cases by risk level (Low, Medium, High).
- Human-in-the-loop: Defining where manual verification is required for AI outputs.
- Cost Controls: Monitoring and limiting API spend across the organization.
Readiness Audit Guide
Before writing code, we assess where AI can actually move the needle. Our audit process looks at:
- Data Plumbing: Is your data accessible, clean, and structured for RAG?
- Process Mapping: Identifying high-volume, low-complexity tasks ripe for automation.
- Cultural Readiness: Assessing team sentiment and identifying internal AI champions.
More Coming Soon
We are currently migrating our internal playbooks and technical guides to this documentation site. Check back soon for deep dives into RAG architectures, Agentic workflows, and custom LLM evaluation.