The four practices reinforce each other. Legal removes the work nobody should be doing; enablement makes your people ready to use what replaces it; custom development builds what does not exist yet; and security is threat-modelled into all three before anything touches client data. Most firms start with one repetitive process everyone complains about, and end up with a programme.
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The AI company in Mauritius for firms that can't afford to get it wrong.
Law firms, accountants and financial services businesses run on confidential work and finite hours. We automate the repetitive part, build the systems that don't exist yet, and secure both. We made Themis. Now we do it for your firm.
We are an AI company in Mauritius, based at Vivéa Business Park in Saint-Pierre. Legal AI is where we started: Themis is trained on the complete published corpus of Mauritius law, 4,100+ Acts, 57,000+ Supreme Court and Privy Council judgments and 17,800+ regulations, with a citation on every answer. If you are weighing up legal AI for a Mauritian practice, start with the complete guide to legal AI in Mauritius; if you are choosing a supplier, read what an AI company in Mauritius actually does.
Three things, done properly. Most firms need all three eventually, most start with one.
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Built in Saint-Pierre, Mauritius, for a jurisdiction that works across borders. Our clients' matters run into Africa, India, the Gulf and the European financial centres, and the systems we build have to hold up in every one of them.
Port Louis
Johannesburg
Nairobi
Dar es Salaam
Cape Town
Maputo
Antananarivo
Mumbai
Dubai
Singapore
Luxembourg
London
We design for professional secrecy from the first workshop, not the post-mortem. Where client data flows, who can see it, what is retained and what is logged goes in the proposal.
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Our security and confidentiality framework
We run an offensive security practice, so we know what an attacker does with a badly configured AI integration. Every system we deploy is threat-modelled before it sees client data.
We work within the Mauritian Data Protection Act and the confidentiality duties your profession already owes its clients.
Before any system is built, we map where client data will travel, which third parties touch it, and what each one retains.
Every integration we ship is threat-modelled, access-scoped and logged, so you can answer a client's due diligence questionnaire with evidence rather than assurances.
We write the AI use policy your staff will actually follow, and the register that shows what went where.
Our practices follow recognised security standards rather than a vendor's marketing checklist.
The deliverable is never just software. It is a firm that knows how to use it, with a written policy that holds up and monitoring that tells you when something changes.
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BUILDING AI YOUR CLIENTS CAN TRUST
Adoption fails on habits, not on models. We start with what your staff are already doing, then make the right thing the easy thing:
Training people will actually attend
A written AI use policy
Shadow AI, surfaced not punished
Role-based access to every tool
Champions in every team
We map the work before we change it, so the sequencing is evidenced rather than argued. You keep something concrete after each stage:
Process inventory, timed and costed
Ranked automation roadmap with ROI
Two-week build sprints
Runbooks and documentation
Monitoring and periodic review
Technology is the last decision, not the first. Whatever we build is scoped, logged and traceable back to a source:
Systems built for how your firm actually works
Threat-modelled before it touches client data
Scoped, least-privilege access
Full logging and audit trail
Every output traceable to its source
Data-flow mapping across third parties
Integration with the systems you already run
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WHAT MAKES US DIFFERENT
We build products, not just integrations, and we finish by training your people.
Themis required indexing the entire published corpus of Mauritian law: 4,100+ Acts, 57,000+ judgments, 17,800+ regulations. Most of what we do for clients is far simpler than that, which is exactly the point. We answer in minutes what takes a pupil a day, and every answer cites its source.
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HOW AN ENGAGEMENT ACTUALLY RUNS
No twelve-week discovery. No proposal full of maybes. Four stages, and you keep something concrete after each one: Map, Rank, Build, Embed.
Map
Two weeks inside the firm. We time every repetitive task and cost it. You keep a process inventory with hours and cost per task, whether or not you commission anything further.
Rank
We score every candidate process on effort, risk and return. You keep a ranked automation roadmap with the ROI per item, so the sequencing decision is yours and it is evidenced.
Build and embed
Two-week sprints, then training and governance. You keep deployed automations, documentation and runbooks, plus trained staff, a written AI policy and monitoring.
Map
Two weeks inside the firm. We time every repetitive task and cost it. You keep a process inventory with hours and cost per task, whether or not you commission anything further.
Rank
We score every candidate process on effort, risk and return. You keep a ranked automation roadmap with the ROI per item, so the sequencing decision is yours and it is evidenced.
Build and embed
Two-week sprints, then training and governance. You keep deployed automations, documentation and runbooks, plus trained staff, a written AI policy and monitoring.