AI integration and AI automation for your business

What AI is good at in business software — and what it is not

Large language models are good at reading and writing text: answering questions from documents, summarizing, extracting fields, classifying requests and drafting replies. They are not reliable calculators, they can be confidently wrong, and they should not make irreversible decisions alone. We design every AI feature around that: the model proposes, your system checks, and a person approves where the stakes are high.

How an AI project runs

1. Pick one job. A specific task with a clear before/after — for example, “answer 60% of support questions from the help center” or “turn supplier invoices into records”.
2. Build a test set. Real examples with correct answers, so quality is measured, not guessed.
3. Prototype in 1–2 weeks on your data, compare models, and decide whether it is good enough to ship.
4. Integrate and launch inside your CRM, product or chat channel, with logging, limits and a fallback to a person.

Data and privacy

API keys, logs and data stay in your accounts. We use providers’ business APIs, which by their published terms do not train on API data by default, and can use open models on your own infrastructure when data must not leave it. Access to documents follows the same roles and permissions as the rest of your system.

Related services

AI features usually sit inside a larger system: a custom CRM, a web application or a business automation. See also how we work.