Most AI projects stall because they start from the technology instead of a problem worth solving. We begin by identifying a use case with a measurable return, prove it in a short pilot, and only then invest in scaling it.
What we deliver
- Use-case discovery workshop with an ROI model before development
- Data readiness assessment — what you have and what is missing
- AI chatbot and document assistants built on your own knowledge base
- Computer vision, forecasting and classification models
- Deployment with monitoring so model quality is tracked over time
How we work
- Use-case discovery & ROI modeling
- Data readiness assessment
- Pilot delivery in 6–8 weeks
- Production MLOps deployment
- Continuous model monitoring
Technology we work with
OpenAIAnthropic ClaudeLangChainLlamaIndexPyTorchTensorFlowHuggingFacePinecone
Frequently asked questions
How much data do we need before we can start with AI?
It depends on the use case. A chatbot answering from internal documents can start with what you already have, while forecasting needs quality historical data. We always assess data readiness first.
Will our data be exposed to the AI provider?
We design for control — from using services that do not train on your data, through to deploying models inside your own environment for highly sensitive information.
How long before a pilot shows results?
Typically 6–8 weeks, with success criteria agreed up front so you can make a clear decision on whether to scale.
