Services
We take on entirely new systems as well as extensions to existing ones built by other teams. Scope, price and the responsible team are agreed before we start.
AI Engineering
We put machine learning and LLMs into products people actually use: retrieval over your own documents, classification and extraction, and forecasting. Every engagement includes a measurement step before delivery.
AI-powered Products
Web platforms where AI capability is part of the product rather than a demo bolted onto the page — assistants, search, ranking and automation inside day-to-day workflows.
Mobile Apps
iOS and Android apps, native or from a single codebase with React Native and Flutter, using on-device AI or API calls as the case requires.
Cloud & MLOps
Architecture and automation on AWS, Azure and GCP — from containers and CI/CD to model serving, monitoring and drift detection in production.
FAQ
Work that requires interpreting language or large volumes of data: answering questions from internal documents, extracting data from files or email, categorising requests, forecasting trends. We start with an assessment. If simple rules or a process change would serve you better, we say so.
With a conversation. Tell us the problem, your timeline and the budget you have in mind, and we reply with a straight assessment of what to do, what to skip and roughly what it will cost. If it fits, we move straight into defining the scope.
Usually, yes. We start by reviewing the existing code and system — architecture, data, security and deployment — then give you a clear recommendation: extend it, refactor it or rebuild it.
Every project includes a support period after launch for fixes and monitoring. AI work also gets quality and drift monitoring; after that you can choose a monthly support plan or take the work in-house, with the full code, documentation and configuration.
Tell us briefly what the project looks like, and we will reply with feedback you can act on.