Artificial intelligence consulting: our six areas of expertise
From strategy to team training, Orthodrome covers the entire AI value chain — or only the segment your company actually needs.
We build first. The rest follows if you need it.
A website, an application, a line-of-business tool: that is where most projects start. Consulting, infrastructure and training exist too — we do not sell them up front.
Websites & bespoke software
A website that works for your business, an application that replaces a spreadsheet, a line-of-business tool that exists nowhere else. Built to last, not to demo.
We write code built for someone else to take over: readable structure, choices justified in writing. The technologies are proven: you depend neither on one vendor nor on us. Automated tests cover the critical paths: a regression surfaces before release, not after. Every release goes through acceptance on a separate environment, with a documented rollback. A prototype exists to decide, a product exists to work with: we never deliver one in place of the other.
AI consulting & expertise
Audit, scoping, roadmap. We pinpoint where AI creates value — and, above all, where it does not.
The audit starts with your actual processes, not the tools on the market. We interview the teams and assess your data: no model compensates for data that is missing or wrong. Every use case is weighed on three axes: value, feasibility, legal and human risk. GDPR and the EU AI Act enter the analysis here, not after go-live. You leave with a prioritised roadmap — discarded use cases included, with the reason for each decision.
Solution integration
Putting AI into production within your tools and workflows: measured, documented, reversible.
A successful integration shows up in the tools your teams already open: email, CRM, ERP. We start narrow, with success criteria agreed before the work begins. Every model call is logged and capped: you see usage and running costs. Sensitive decisions stay with a human: the AI proposes, your teams decide. A documented way back exists, with no loss of data. A tool nobody opens is a failure, even when it works perfectly.
Technical infrastructure
Design, administration and maintenance of reliable, secure and sovereign infrastructure.
Without stable infrastructure, capable AI stays a demonstration. We design environments hosted in Europe when data sensitivity demands it, running open models on your own servers rather than sending documents to a third party. Access is compartmentalised, traffic encrypted. Restoring backups is tested: a backup that has never been restored is not a backup. Monitoring surfaces drift before it becomes an incident. Everything is documented so another team could take over without us.
Process optimisation
We shorten the distance between intent and result: automation, organisation, performance.
We observe the work as it is actually done, not as the procedure describes it: the gap is usually where the losses sit. Every step is measured — waiting time, duplicate entry, approval round trips. Automating a broken process only accelerates the mess: we remove and simplify before we automate. Gains are tracked with indicators agreed at the outset. The people who do the work help redesign it: they know the exceptions the documentation never recorded.
Training
Your teams brought up to speed. After we leave, it runs without us.
Training runs on your files and your tools: generic exercises rarely survive the return to the desk. Sessions are shaped by role — leadership learns to decide, teams learn to do. We cover the limits too: what a model invents, what must never leave the company. Internal reference users take over everyday questions once we step back. Every session leaves written material and reusable examples. The goal is your autonomy, not dependence on us.
So where do you start?
Describe your situation: you get a heading, a scope and a quote in return. No commitment.
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