Start with one repetitive, text-heavy process (support replies, lead qualification, document extraction), connect an LLM such as GPT or Claude to your own data with RAG, run a 1–3 week pilot on real data, measure the result, then scale. Development for a pilot is typically 40–160 hours; API usage is usually a small monthly cost.
Where AI pays off first
- Customer support assistant answering from your documentation
- Lead qualification and instant replies to inquiries
- Extracting data from invoices, contracts and forms
- Internal knowledge assistant for staff
- Summarising calls, e-mails and tickets
- Drafting proposals, product descriptions and reports
- Computer vision: inspection, counting and measurement from photos or drone imagery
Approaches
| Approach | When to use |
|---|---|
| Ready-made AI tools | Individual productivity, no integration needed |
| LLM API integration | AI feature inside your product or workflow |
| RAG (retrieval-augmented generation) | Answers must come from your own documents and data |
| AI agents | Multi-step tasks that call your systems (CRM, tickets, e-mail) |
| Self-hosted open-source models | Data must not leave your infrastructure |
| Fine-tuning | Rarely needed; only for very specific style or classification tasks |
Step by step
- Pick one process and measure the baseline (time, cost, errors)
- Collect real examples and documents
- Build a pilot in 1–3 weeks
- Evaluate quality on real cases with your team
- Add guardrails: citations, human review for sensitive actions, logging
- Roll out and monitor quality and cost
Risks and how to manage them
- Wrong answers (hallucinations): use RAG with sources, limit scope, keep a human in the loop
- Data privacy: use providers that do not train on your data or self-host
- Cost: cache, choose the right model size, monitor usage
Amsoft
Amsoft builds AI assistants, RAG chatbots, AI agents, n8n automations and computer-vision solutions. A pilot on your data is usually ready in 1–3 weeks; rates start from $25/hour.