Solutions / Large enterprises
A small studio that moves quickly and comes prepared for your security review.
These scenarios are illustrations. None of them describes a client.
Banking and finance
What we would build
An agent that gathers the client file from each system, checks expiry dates and missing items, and drafts the review summary with its sources. The analyst signs off on the complete file, and the agent has no permission to contact clients or approve anything.
LangGraph, Python, PostgreSQL, Avaloq API
Pharma and life sciences
What we would build
A search assistant over your submissions, SOPs and Swissmedic, EMA and ICH guidelines that answers in a few sentences and links each claim to the exact section. It is read-only, and it declines to answer when the documents do not support one.
FAISS, bge-reranker-v2-m3, vLLM, Veeva Vault
Watchmaking and luxury
What we would build
An inspection station that photographs each dial under fixed lighting and highlights areas that differ from approved parts. Inspectors confirm or overrule each flag, and those decisions become the reference for the next model update.
PyTorch, Anomalib, ONNX Runtime
Retail and e-commerce
What we would build
A service agent that reads each ticket, looks up the order and the return policy, and drafts the reply in the customer's language. Routine answers go out after a quick check; refunds and exceptions wait for a person, with the case already summarised.
LangGraph, Zendesk API, FAISS
Banking and finance
What we would build
A screening assistant that groups hits by the person they actually describe, using the birth dates, places and employers mentioned in each article. Analysts review one card per real person with the matching evidence highlighted, and every dismissal is logged with its reason.
Python, spaCy, Mistral, PostgreSQL
In a large organisation the model is rarely the hard part. Access to data, security approval and handover to an internal team decide whether a project reaches production, so we plan for them from the start.
A senior engineer from our side working with your product owner, a data owner and someone from IT or security.
A fixed-price feasibility study first, then a scoped build phase once the results are known.
We prepare the material your architecture board, security and procurement need, in the formats they use.
A working prototype on your data with a written assessment of what production would take.
Yes. We budget time for vendor assessments and security reviews in the plan, and prepare what they usually ask for: architecture, data flows, hosting and access rights.
That is the default. Code, documentation and runbooks are yours, and we pair with your engineers before handover.
Yes. We can develop and deploy inside your cloud tenant or data centre with accounts you provide.
Feasibility studies are fixed price. Build phases are scoped on the study results, either fixed price or time and materials.
We start with a feasibility study on your own data, so you see results before anything is promised.