Ship AI products. Not proofs of concept.
We design, build, and operationalise AI systems for enterprise teams — private LLMs on AWS Bedrock, retrieval pipelines, agents, MLOps, and domain copilots that run in production with audit trails and SLAs.
Sound familiar?
- 01Your AI pilot worked in a notebook but never made it to production.
- 02Off-the-shelf copilots miss your industry vocabulary and data model.
- 03Public LLMs are a non-starter for your data residency or compliance boundary.
Concrete outputs. Nothing hand-wavy.
How we run the engagement.
Discover
Use-case scoping, data access, success metrics, eval design.
Design
Model + retrieval architecture, UI contract, security boundary.
Build
Ingest, index, integrate, test against eval harness.
Operate
Production deploy, monitoring, retrain cadence, handover.
Opinionated but pragmatic.
We are deepest on AWS and Claude / Bedrock. We also ship on Azure, GCP, and open-source where they are the right fit.
- Claude on Bedrock
- Llama 3 / Mistral self-hosted
- Fine-tuned OSS
- OpenSearch
- pgvector
- Pinecone
- custom hybrid
- LangGraph
- LlamaIndex
- custom agent runtimes
- Ragas
- DeepEval
- domain-specific harnesses
Pick a model. We make both work.
Zero upfront. We co-invest the engineering and earn through revenue share or equity once the product is live.
$0 upfront
From $60,000 per product · Partnership model available
Retainers from $14,000/mo for ongoing engineering capacity.
Frequently asked.
Ready to scope your AI / GenAI Engineering engagement?
Book 30 minutes with our team — we will tell you honestly whether the partnership model fits or whether an SOW is the better path.