AI development services
AI that shipsinto the product, not into a slide deck
We build AI features that live inside real software — retrieval over a company's own documents, tenant-isolated knowledge bases, and model gateways that keep working when a provider goes down.
500+
Projects delivered
most under NDA
100+
Clients served
5 regions
5
Systems live
in production now
—
Clutch rating
awaiting verified score
What we build
The work itself,component by component
Retrieval-augmented platforms
Ingestion, chunking, embeddings, and a vector store your team controls, so answers cite your documents instead of the open web.
Multi-LLM gateways
One interface in front of several providers, with routing, retries, and cost accounting per tenant.
Tenant-isolated knowledge
Every query is scoped to one customer's corpus at the storage layer — not filtered after the fact.
Evaluation harnesses
Golden question sets and regression runs so a prompt change cannot quietly make answers worse.
Streaming interfaces
Token-by-token UI with cancellation, retry, and a trace panel that shows which sources were used.
Deployment into your cloud
The system runs in your AWS account under your keys. We hand over the infrastructure, not a hosted black box.
Why it matters
What changesonce it is running
Three things a buyer of this work should be able to hold us to.
Answers you can audit — Every response carries the source chunks it was drawn from, so a wrong answer is diagnosable rather than mysterious.
No vendor lock — The gateway means swapping a model is a config change, not a rewrite.
Built by the people who run it — The engineers who design the retrieval layer are the ones who keep it alive afterwards.
Stack we use for this
- Python
- FastAPI
- AWS Bedrock
- OpenSearch
- LangChain
- PostgreSQL
- Docker
- Next.js
How it runs
Four stages,and you can leave after any of them
Scope
We agree what the system does and what shipping means, in writing.
Build
Short cycles in your repository, running before it is finished.
Ship
Deployed into your cloud account, reachable by a real user.
Stay
Maintenance and roadmap by the same engineers who built it.
Proof
The systemsthat back this page
FAQ
Questionswe get asked
Do you use our data to train models?
No. Your corpus is used for retrieval only, inside infrastructure you own. Nothing is sent to a training pipeline.
Can this run entirely in our cloud?
Yes — that is the default. We deploy into your account so the data never leaves your perimeter.
What if the model provider changes pricing?
The gateway abstracts the provider. Routing to a different model is a configuration change.
AI development services