WHAT WE BUILD
Services
Six ways we help engineering teams ship faster with agentic AI. From open-source frameworks to hands-on implementation.
Clarity Framework
An agentic intelligence framework for technical engagements. Built on Karpathy's LLM Wiki pattern, extended with structured operational data and behavioral memory.
View on GitHub- Self-learn loop — observations auto-validate and promote into structured knowledge
- Wiki system with Obsidian-compatible cross-linking
- 9 slash commands for SE workflows (discover, brief, check, self-improve)
- 6 reusable engineering patterns (correlationId, idempotency, error handling)
- Client templates with expertise.yaml, phase-0 docs, and note-taking
- Three knowledge systems: operational YAML, behavioral memory, durable wiki
AI Integration Consulting
We wire AI into your existing stack. Config-driven pipelines, API connectors, workflow automation with n8n/Make/Zapier, and custom integrations that actually work in production.
Get in Touch- Config-driven pipeline architecture — swap providers without code changes
- API connector development for any service (REST, GraphQL, webhooks)
- Workflow automation (n8n, Make, Zapier) with error handling and retry logic
- Data transformation and enrichment pipelines
- Production monitoring and alerting setup
- Migration from manual processes to automated workflows
Claude Code Implementation
Custom Claude Code setups for your team. Skills, slash commands, memory systems, MCP servers, and hooks that make your engineers 10x more effective with AI.
Get in Touch- Custom slash commands tailored to your codebase and workflows
- Memory systems that persist context across sessions
- MCP server integration for your internal tools and APIs
- Hook configurations for automated quality checks
- Team onboarding and training on agentic development
- CLAUDE.md architecture for project-specific AI behavior
Knowledge Base Builder
Structured knowledge that compounds over time. We build wiki systems that make your team smarter with every interaction — from intake to synthesis to retrieval.
Get in Touch- Obsidian-compatible wiki with cross-linking and tagging
- Raw file intake pipeline (web clips, transcripts, PDFs, Slack threads)
- Auto-generated index with per-page summaries for LLM navigation
- Processing log for audit trail and traceability
- Health checks: orphan detection, broken links, stale content alerts
- Query-to-wiki loop — good answers get filed as permanent knowledge
Document Processing Pipelines
Turn unstructured documents into structured, searchable knowledge. PDFs, meeting transcripts, web clips, email threads — all normalized and connected.
Get in Touch- Multi-format ingest (PDF, DOCX, HTML, Markdown, plain text, images)
- Hybrid AI approach — use the right model for each task
- Entity extraction and relationship mapping
- Structured output with consistent schemas
- Integration with existing search and retrieval systems
- Processing pipeline with retry logic and error recovery
Build in Public
We share everything we learn. Open source contributions, technical blog posts, and transparent engineering. Follow the journey and learn alongside us.
Read the Blog- Open source framework development on GitHub
- Technical blog posts on agentic AI patterns
- Walkthroughs of real implementation sessions
- Community contributions and pattern sharing
- Conference talks and workshop materials
- Weekly progress updates and learning logs
Let's build something
Every engagement starts with a conversation. Tell us what you're building.
Get in Touch