01AI Development
Custom LLM integrations, RAG systems, AI agents and document-intelligence pipelines — scoped conservatively, evaluated honestly, owned by you.
How it flows
- LLM01
- Retrieval02
- Business data03
- Response04
01Overview
- OpenAI
- Anthropic Claude
- LangChain
- Pinecone
- Supabase Vector
- RAG
- AI Agents
Most AI projects fail not because the model was wrong, but because the surrounding product system wasn't built for real data, edge cases, permissions, latency and user trust.
We build AI systems engineered for production: custom LLM integrations, retrieval-augmented generation, agents, document workflows and internal copilots that connect cleanly to your existing tools.
We define evaluation criteria before launch. The goal is not a demo that sounds impressive once — it is a system your team can trust, monitor, improve and own.
02What we ship
- LLM integrations into existing products
- RAG pipelines over private company knowledge
- AI agents with tool use and audit trails
- Internal copilots for support, ops and sales
- Document intelligence & summarization
- Evaluation frameworks with acceptance thresholds
Key deliverables
- Custom LLM integration with your product or data
- RAG pipeline with accurate retrieval over your corpus
- AI agent workflows with tool use and audit trails
- Evaluation framework with acceptance thresholds before launch
What's included
- LLM integration (OpenAI / Claude / open-source)
- RAG pipeline (LangChain + Pinecone / pgvector)
- Prompt engineering & context management
- Eval dashboard & cost monitoring
03Process
Discover & Scope
Review your data, define what “correct” means, set accuracy targets. Output: evaluation rubric, risk map and scoped build plan.
Build & Evaluate
Sprints with weekly demos. Every increment is evaluated against agreed thresholds before we move forward.
Validate & Hand Off
Production deployment with cost monitoring, eval dashboards and full handover of prompts, pipelines and infrastructure.
04Related work
05Questions
Planning, architecture, development, integration, deployment and monitoring of AI systems — LLM workflows, RAG applications, agents, copilots and document-processing pipelines.
06Related services
07Start a project
Tell us what you're building, where you are today, and what needs to happen next. We'll come back with a technical point of view — not a sales pitch.
- Response within one business day
- Scoping workshop available within the week
- Worldwide, remote-first