BOOTINGJRV//SYSTEMS/
AI that earns its keep.
AI integration means connecting a model — Claude, GPT or Gemini — to a specific job inside your business, with access to your own documents and systems, so that it answers from your data rather than from the open internet.
Claude, GPT, Gemini — wired into your business workflows. Internal copilots, customer-facing assistants, document automation, RAG over your knowledge base. Not chatbot toys. Real productivity tooling.
Almost every AI project that fails does so the same way: a chat box gets added to a website, it knows nothing about the business, and within a month nobody uses it. The model was never the problem. It had no access to anything worth knowing.
The work that pays for itself is duller and further inside the company. Someone spends two hours a day reading delivery orders and typing their contents into a system. Someone else answers the same eleven questions from customers every week. A quotation takes forty minutes because the numbers live in four places. Those are the jobs a model does well, because the answer is already in a document you own.
The second half of the work is knowing where it must not be trusted. A model that guesses a price, invents a stock level or confirms a compliance status is worse than no model at all. We wire the boundary deliberately: retrieval from your data, a refusal path when the answer is not there, and a log of what it did.
We look for something a person does more than twenty times a week where the input is text or a document. That is the shape of a job worth automating. If nothing in the business looks like that, we say so rather than build a demo.
Usually the hardest step. PDFs, spreadsheets, an accounting export, five years of WhatsApp threads. We extract, clean and index it — pgvector or Pinecone — so retrieval returns the right paragraph rather than a plausible one.
Cheap fast models for classification and routing, frontier models for reasoning and drafting. Most systems we ship use two or three and route between them, which is what keeps the monthly bill sane at volume.
Tool access is explicit, the prompt states what it must refuse, and every call is recorded with its inputs. When someone asks why it said that in March, there is an answer.
Time per task before and after, on real work, for a fortnight. If the number does not move we would rather find that out in week two than at the end of a retainer.
AI work is usually scoped as a module inside a build or as its own project. The WhatsApp assistant is the one we price off the shelf because we have shipped it repeatedly.
The published add-on rate: a working assistant on your number, wired to your data, with admin commands and logging. Model usage billed at cost.
Extraction and routing for one document type at volume — delivery orders, invoices, claim forms — including the review screen a person needs when it is unsure.
Enterprise tier. Copilots and retrieval built into a full application, with role-scoped access and an audit trail.
Two longer answers sit outside the service pages: the reference guides on the LHDN e-Invoice phases and what each route into MyInvois costs, and the sector notes on what each sector's day-to-day record has to hold before software touches it.
