HEXIT · AI Engineering & Advisory
We are a team of senior specialists who have spent years inside banking, aviation, healthcare and logistics, among others. Companies bring us in to figure out where AI and modern technology genuinely help, and where they don’t. Most of what we do is advisory. When a problem needs building, not just advice, we solve it end to end for the client in front of us.
Our premise
We design, build, and govern production AI for organisations where a wrong answer has real consequences. Banking, aviation, healthcare, and the back office that runs everything else.
Point of view
Most AI is rented. You send your data to someone else’s model, on someone else’s infrastructure, under someone else’s terms. And you rebuild your workflow every time their pricing or policy changes.
Sovereign AI is the opposite. The models, the weights, the data, and the deployment sit inside your boundary. You can read every decision, reproduce every result, and answer a regulator without a phone call to a vendor. For a bank, an air-navigation provider, or a hospital, that isn’t a preference. It’s the line between a system you can deploy and one legal won’t sign off on.
We don’t treat this as ideology. SaaS AI is the right call when speed matters more than control and the data isn’t sensitive. Sovereign AI is the right call when it isn’t. Our job is to tell you which is which, model by model and workload by workload, and to build whichever one you actually need on open-weight foundations you’re free to move, host, and audit.
What we do
Know where AI helps, and where it doesn’t.
From a slide to a working system.
AI across the delivery lifecycle.
Your team runs it after we leave.
Advisory & Knowledge
The field moves weekly and most of the noise is marketing. We give your leadership a grounded view of what’s real, what it costs, and what it changes for your business, so decisions get made on fact rather than on the last conference talk.
We map what you already run: models, data flows, cost, risk, and the shadow AI nobody put on the roadmap. Then we hand you a prioritised picture of what to fix, keep, and switch off. You leave with a decision document, not a deck.
Working AI is rarely finished. We take systems that are already live and make them cheaper, faster, and more accurate. That means right-sizing models, rebuilding pipelines, cutting inference cost, and putting evals in place so quality stops being a matter of opinion.
Build
You have a hypothesis; we turn it into something you can click. In weeks, not quarters, we build a proof of concept on your real data. Enough to prove the value, kill the bad ideas early, and give you something concrete to take to a board.
When the PoC earns its place, we build the production version: hardened, observable, and integrated with the systems you already run. No throwaway prototype dressed up as a product.
We build agents that do real work: tool use, multi-step reasoning, and orchestration across systems, all with the guardrails, evaluation, and human-in-the-loop controls that keep autonomous software trustworthy. We know where they break and how to stop them.
Embed
AI isn’t a feature you bolt on at the end. We put it to work at every stage of how software gets built, and we’ve done it inside regulated delivery, so the speed never comes at the cost of the paper trail.
Mine requirements from documents, interviews, and existing systems; surface the gaps and contradictions a human reviewer misses; and turn vague intent into specifications a team can build against.
Agentic coding, automated review, and large-scale migration, used with judgement rather than as a novelty. We know which parts of the lifecycle AI accelerates and which parts it quietly breaks.
Generated test suites, coverage that tracks real risk, and tests that repair themselves when the UI shifts. QA keeps pace with faster delivery instead of becoming the bottleneck.
AIOps that earns its keep: anomaly detection, faster root-cause, and runbooks that write and update themselves. We’ve reverse-engineered enterprise incident-investigation platforms to build equivalents that fit your stack.
The part everyone skips until it’s a problem. Model risk, audit trails, access, and provable compliance, all mapped to the EU AI Act and the frameworks your regulator actually uses. Built in from the start, not retrofitted the week before an audit.
Enable
The best outcome of an engagement is a team that no longer needs us. We run training and workshops on real systems, yours where possible, so your people can operate, extend, and question the AI we build together. Knowledge transfer isn’t a closing formality. It’s the point.
Where we work
Safety-critical, heavily regulated, and where we’ve done our most demanding sovereign-AI work. We understand air-navigation constraints, not just the acronyms.
Model risk, auditability, and data that can’t leave the building. AI that passes second-line review.
Clinical-grade caution: privacy, safety, and systems that fail safely when they fail at all.
Back-office automation and decision support for freight and supply chains. The unglamorous work that moves margins.
Generative content and creative pipelines that scale without losing the brand.
AI on top of the systems that run the company: SAP and the record-keeping backbone.
On-device and edge AI, where the model runs in your hand and the data never leaves it.
New domains on request. The engineering transfers; the regulation is what we learn per sector.
Contact
Tell us the real, messy problem. We’ll tell you whether AI is the answer, and if it is, we’ll build it.