01 · Process automation
Order requests
Orders arriving by email, as PDFs, on WhatsApp. An agent reads them, checks prices and availability in the ERP and prepares the order for confirmation.
// use cases · 11 scenarios
Eleven problems we solve with AI.
We picked them from the ones companies ask us about most often. For each one we explain where things start, how we step in and which indicators we use to measure the result.
We set the goals together, in discovery, starting from your data.
Sales
02 scenarios02 · LLM integration
Quotes and estimates
Specifications, drawings, three-line requests: for anyone working to order, every quote is a job in itself. AI finds similar past jobs and proposes line items, times and costs to validate.
Front office and admin
02 scenarios03 · Process automation
Email triage
The info@ inbox receives everything and someone has to sort it by hand. AI reads every email, gives it a category and forwards it to the right department. It replies to nobody: it routes.
04 · Process automation
Document analysis
Delivery notes, supplier confirmations, contracts, certificates. AI recognises every document, extracts the data for the ERP and flags what a person needs to look at.
Customers and support
02 scenarios05 · RAG and knowledge base
Document assistant
Customers and colleagues ask questions, and the assistant answers using only your documents and the pages of your website. Every answer comes with its source, and when it does not know, it says so.
06 · RAG and knowledge base
Technical support
Manuals, technical sheets and resolved tickets become answers with the source next to them, for the technician on site and for whoever answers the phone.
Management
02 scenarios07 · MCP servers
ERP assistant
How the month went, which orders are stuck, what is missing from stock. Questions in plain language to the assistant you already use, with the answers taken from the ERP.
08 · Fractional AI/CTO
AI roadmap for SMBs
Everyone is pitching something with AI and nobody in the company can evaluate it. A technical counterpart who lines up the use cases and decides with you what to buy and what to build.
Software teams and startups
03 scenarios09 · Process automation
Sprint reports
Closed tickets, commits and pull requests become the end-of-sprint report and the release notes, in two versions: technical for the team, readable for clients and users.
10 · LLM integration
User behaviour
Application logs and databases already show how people use them, but nobody has time to read them. AI reads them, writes a report and suggests what to improve.
11 · AI-first MVP
AI product from scratch
An idea with AI at its core, a market to validate and no technical team. A real product in a few weeks, with real users, built to be able to change.
Yours is not here?
Quite likely: these are the most frequent, not the only ones. If a process costs you hours every week, tell us about it and we will tell you whether it is a use case or not.
Thirty minutes to find out whether yours is a use case.
A free call. If AI is not needed, we will say so.