Cognitive Carpentry – Applied
You own the domain. We bring the AI.
We integrate AI into your applications so your knowledge becomes usable – without changing how you work.
Built with the discipline of software engineering. Delivered with the care of craftsmanship.
How We Work
How we work with clients from discovery to operation.
Discovery
Use Case Discovery & Integration Design
We analyze your domain, your applications, and your data to identify where AI creates value.
- Map your knowledge landscape (documents, data, gaps)
- Identify integration points in your applications
- Prototype on your data to validate feasibility
- Define an architecture that fits your stack
Typical engagement: 2–4 weeks
Build & Integrate
AI Backend Deployment & Integration
We deploy Ex-Libro and integrate it into your systems.
- Deploy on your infrastructure
- Integrate via API into your applications
- Set up knowledge pipelines (ingestion, indexing)
- Connect structured data and APIs
- Design agents (flows, guardrails, grounding)
Your applications stay yours. We power the intelligence layer.
Operate
Managed AI & Continuous Improvement
We keep the system accurate, relevant, and performant.
- Scale and upgrade the platform
- Maintain knowledge pipelines
- Monitor retrieval quality
- Tune agents based on usage
Why This Model Works
You don’t need to build an AI team.
We bring a production-ready platform and the engineering expertise to integrate it properly – across APIs, databases, and real systems, not just documents.
You keep control:
- your applications
- your data
- your user experience
We built Ex-Libro ourselves. You work directly with the engineers who designed it.
Ways We Work
We offer three engagement models.
Fixed scope
Defined deliverable
Assessments, prototypes
Time & materials
Ongoing collaboration
Integrations, custom work
Retainer
Reserved capacity
Continuous improvement
Areas of Expertise
AI Engineering
RAG systems
Agentic workflows
Conversational AI
Knowledge pipelines
Software Engineering
API design and system integration
Enterprise architecture and multi-tenant systems
Typescript / Python / Java
NestJS / Node.js / React / PostgreSQL / Docker
Hexagonal architecture, event-driven systems
Data Science
Machine learning engineering
Predictive maintenance and anomaly detection
Time series analysis
Evaluation and quality metrics for AI systems
Let’s scope your integration
Tell us about your domain and your applications. We’ll show you where AI fits – and how to get there.