Suggestions, classification, document processing: built into your application with Spring AI or LangChain4j. Models run entirely at your site if you want.
A separate AI tool means a context switch, and context switches get avoided. AI becomes useful when it appears in the work step itself: the suggestion sits in the form, classification happens on upload. With open libraries in the Java or Go stack it stays part of your application — not a foreign body.
One concrete step that costs time today and has clear criteria. Not a chatbot for everything, but a function that measurably relieves work.
Your documents and data become searchable via pgvector or OpenSearch. Answers come with a source, not from the model's memory.
Spring AI or LangChain4j integrates the model into your business logic. Permissions, logging and error handling follow the same rules as everything else.
What the model may do is in the code. Automated tests check quality and unwanted output before a change goes live.
if needed: open models on your own hardware, your data stays with you.
instead of from the gut: every answer shows what it came from.
not beside it: AI follows the same permissions and logs as your domain logic.
All open source — no licence costs, no lock-in.
30-min intro call — free.
No standard pitch. I listen, ask the right questions and give an honest assessment — even if we are not the right partner.
