AI that does real work, and proves it

The pilot is a fixed-price, 3–4 week engagement scoped to one workflow. Running costs depend on how often the AI is used and which model each task needs, so we estimate them per task during the pilot and show them on a cost dashboard. Before you scale, you see the real monthly cost next to the hours or errors it saves.

No. We only use model providers whose business terms say your data is not used to train their models, and we configure accounts accordingly. Where data must stay in your own environment, we can use open models hosted in your cloud. We also minimise and mask personal data before it reaches any model.

We ground answers in your own documents and show the sources, so people can check them. Before launch we build an evaluation set from real cases and score accuracy, and we re-run it after every change. For anything high-stakes – payments, deletions or replies to customers – a person approves the action first.

The one that fits each task on cost, quality and data rules. We work with OpenAI, Anthropic Claude, Google Gemini and open models such as Llama and Mistral. A pilot often mixes them: a small, cheap model for routine steps and a stronger one for hard cases. Because the evaluation set is yours, switching models later is a measured decision.

Usually, yes. We connect to CRMs, help desks, email, WhatsApp Business, spreadsheets, databases and internal APIs, so people keep working where they already are. We use each tool's official API or the Model Context Protocol, with the minimum permissions the workflow needs, and log every action the AI takes.

Then you've learned that cheaply, in four weeks. The final report shows the measured result against the baseline and explains why it fell short, whether that is data quality, process or model limits. You decide to change the approach, try a different workflow, or stop. You keep the code, the evaluation set and the findings either way.

It can be, with the right design. We collect only the personal data a workflow needs, mask it where possible, respect the consent your users gave, and use providers that don't train on your data. Access is logged and limited by role. We document data flows so your legal team can confirm compliance; we don't give legal advice ourselves.