AI Integration
We are not interested in adding a chat bubble. We pick one repetitive, measurable, text-heavy job and automate it — in a way where you can see the result as a number.
Who is it for?
- Companies whose support volume has outgrown the team
- Organisations struggling to search across their internal documents
- Teams spending hours producing content, reports or summaries by hand
- Software companies adding an intelligent layer to an existing product
What's included?
Choosing the use case
We go through your current processes and pick the highest-return, lowest-risk job together. Picking the wrong job is the most expensive mistake.
Data preparation
Collecting, cleaning and making searchable your documents, catalogues, FAQs and past correspondence.
RAG architecture
A system that finds the relevant passages in your own data and answers based only on those. Every answer shows its source underneath.
Evaluation set
A test suite that measures quality against the same set of questions after every change. Without it, the product quietly degrades with each update.
Human approval step
In critical flows the model's output is never applied directly; it goes to approval. As trust grows, the level of automation goes up.
Cost control and monitoring
Model tiering, caching, budget ceilings and usage limits. No surprise invoice at the end of the month.
How long does it take?
A pilot for one clearly defined use case takes 2–6 weeks. The main driver of the timeline is data preparation.
For budget ranges you can read our guide to software project costs. A firm number comes out once the scope is written down.
Work built with this service
Frequently asked questions
Is our data safe — will it be used to train the model?
On enterprise API plans your inputs are not used for model training, and this is confirmed in the provider's contract. Text containing personal data is masked before it is sent. For sensitive scenarios, open models running on your own infrastructure can also be considered.
What if the AI gives a wrong answer?
The system is built to hand over rather than invent when it cannot find a source, and every answer shows which document it came from. In critical flows human approval is mandatory. On top of that, accuracy is measured continuously with the evaluation set.
What will it cost per month?
Cost depends on usage volume and can be brought down significantly by architectural decisions: routing simple jobs to smaller models, caching repeated questions and batching work that isn't time-critical typically saves 40–70%. A budget ceiling and usage limits are part of the setup.
Which model do you use?
It depends on the job; we prefer the smallest model that is good enough for each one. The model choice is not baked into the code — it sits behind a configuration layer, so when a better or cheaper model appears, switching is a one-line change.
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Let's talk about AI Integration
Tell us briefly and we will come back within 48 hours with a scope and a roadmap. No strings attached, free of charge.