01WEEK 1
Discover
Operating-model review, stakeholder interviews, data inventory, current AI / automation stack audit and a clear list of candidate use cases.
// service_01 · ai_transformation
AI Transformation, Automation & Agentic Operations
End-to-end AI for Mauritian businesses — from a single department to your whole company. Strategy, automation, custom AI agents, copilots, RAG, MLOps, ISO 42001 governance, managed operations and the change management your team actually needs.
// what_clients_experience
0%
Manual work eliminated
Across automated departments in our typical 12-month programmes
0x
Faster process throughput
On finance, HR, compliance and customer-service workflows
0 wk
From idea to live AI
Average time-to-production for a scoped use case
0%
ISO 42001-aligned by design
Every Trivanta AI engagement maps to the AI Management System
// capabilities
Six pillars of AI transformation
Strategy through governance through managed operations — every Trivanta AI engagement combines as many pillars as your context requires. Tap a pillar to explore what we deliver.
// strategy · ai_operating_model
Translate AI hype into a business operating model that pays off.
AI maturity assessment
Where your data, processes, talent and governance actually sit today — not a generic survey, a current-state diagnostic with named gaps.
Use-case discovery & scoring
Workshop-led identification of 15–40 candidate use cases across every department, scored by value, feasibility, risk and time-to-impact.
AI roadmap & ROI model
A 12–24 month roadmap with sequenced waves, investment envelope and a defensible ROI model the board can sign off on.
Build vs buy vs API decision
Crisp decisions on which capability to consume via API, license off the shelf, or build proprietary — informed by Mauritian data-sovereignty constraints.
AI Centre of Excellence design
Org design, RACI, governance forums, talent plan and the operating cadence your CoE needs from day one.
Vendor & platform selection
Independent platform evaluation across Azure OpenAI, AWS Bedrock, Vertex AI, Anthropic, OpenAI, Mistral, Hugging Face and open-source stacks.
// how_we_engage
From discovery to managed operations
A predictable six-step engagement model — designed to de-risk both the pilot and the long arc that follows.
02WEEK 2
Prioritise
Use-case scoring across value, feasibility, risk and time-to-impact. We agree the 12-month wave plan together.
03WEEK 3-4
Design
Architecture, data flows, integration map, governance controls, security baseline and a sprint backlog.
04PHASE 1
Pilot
A 6–10 week pilot on the highest-value use case, with production-grade controls and a measured business case in hand at the end.
05PHASE 2
Scale
Roll out across departments in sprints — each release accompanied by enablement, runbooks and KPIs your operations team can own.
06ONGOING
Operate
Managed operations, evaluations, prompt and model upgrades, cost optimisation, regulatory monitoring and quarterly value reviews.
// technology_stack
A vendor-neutral AI stack — proven and compliant
Foundation models, AI platforms, agent frameworks, automation, vector stores, data platforms, MLOps and governance — every choice driven by your data residency, accuracy, latency and budget needs.
Foundation models
OpenAI (GPT-4o, o-series)
Frontier general-purpose models for chat, agents and reasoning.
Foundation models
Anthropic Claude
Strong reasoning, long context and enterprise-friendly safety posture.
Foundation models
Google Gemini
Multimodal frontier models with strong document and image understanding.
Foundation models
Mistral & Llama
Open-weight models for fine-tuning and on-prem / sovereign deployment.
AI platforms
Azure OpenAI
Enterprise OpenAI with Microsoft 365 / Copilot Studio integration.
AI platforms
AWS Bedrock
Multi-model AI on AWS with guardrails, knowledge bases and agents.
AI platforms
Google Vertex AI
End-to-end ML and GenAI platform on Google Cloud.
AI platforms
Hugging Face
Open-source model hub, inference endpoints and dataset hosting.
Agents
LangChain & LangGraph
Composable LLM apps and stateful agentic workflows.
Agents
LlamaIndex
Production-grade RAG and structured data retrieval pipelines.
Agents
CrewAI & AutoGen
Multi-agent collaboration frameworks for complex tasks.
Agents
Microsoft Copilot Studio
Low-code agents tightly coupled to Microsoft 365 and Power Platform.
Automation
n8n
Self-hostable automation with native LLM nodes — our default for sovereign builds.
Automation
Make & Zapier
Cloud automation for fast time-to-value across SaaS apps.
Automation
Microsoft Power Automate
Enterprise RPA + flow for Microsoft 365 and Dynamics customers.
Automation
Apache Airflow
Data and ML orchestration for repeatable pipelines.
Vector & RAG
pgvector + Postgres
Vector search where you already have Postgres — sovereign and audit-friendly.
Vector & RAG
Pinecone, Weaviate, Qdrant
Managed and self-hosted vector databases for scale-out search.
Vector & RAG
Azure AI Search
Hybrid keyword + vector search with native Microsoft 365 integration.
Data
Snowflake & BigQuery
Cloud data warehouses for analytics, ML features and reporting.
Data
Databricks
Lakehouse for advanced ML, real-time data and AI workloads at scale.
Data
dbt
Modelled, tested, documented analytics transformations.
Data
Apache Kafka
Event streaming for AI features that need fresh data in seconds.
MLOps
MLflow & Weights & Biases
Experiment tracking, model registry and reproducible runs.
MLOps
Kubeflow & Vertex Pipelines
Kubernetes-native and managed pipelines for training and deployment.
LLMOps
Langfuse & Arize Phoenix
Observability, tracing and evaluation for LLM applications.
LLMOps
Promptfoo & Ragas
Automated evaluation harnesses for prompts and RAG quality.
Governance
NeMo Guardrails
Programmable guardrails for LLM applications.
Governance
Garak & PyRIT
AI red-teaming and adversarial robustness testing.
Governance
AI BoM / SBOM tools
Track model, data and dependency provenance for audit and ISO 42001.
// why_trivanta
Why Mauritian operators choose Trivanta for AI
✓
Mauritian context, not Silicon Valley templates
We design for Mauritius-specific constraints from day one — DPA 2017, FSC and BoM expectations, FATF / FIAMLA realities, bandwidth and cloud-region choices, the bilingual customer base, and the local talent market.
✓
Compliance-by-design, not bolted on later
Every AI engagement maps to ISO/IEC 42001 controls and aligns with the EU AI Act and NIST AI RMF. Audit evidence is produced as a by-product of building — not a panic project six months before certification.
✓
Built-in cost discipline
We track token spend, model selection and run cost from day one. Most clients see 30–60% inference cost reduction after our first optimisation cycle — without losing quality.
✓
Vendor-neutral by design
We work across OpenAI, Anthropic, Google, Mistral, Llama and Azure / AWS / GCP. The right model is the one that fits your data residency, latency, accuracy and budget — not the one we resell.
✓
End-to-end accountability
One team owns the engagement from strategy through production operations. No hand-offs between a consultancy that diagnoses, a systems integrator that builds, and a managed-service vendor that operates.
// frequently_asked
AI transformation — straight answers
The questions Mauritian executives ask us most often before, during and after engaging.
Can Trivanta help us set up an AI department from scratch?
Yes. We design the AI Centre of Excellence, write the operating manual, pick the platform stack, hire or train the first analysts and engineers, and run the function on a managed basis until you want to insource. The handover plan is part of the engagement, not an afterthought.
What does an AI transformation actually cost in Mauritius?
A focused pilot on a single high-value use case typically runs MUR 600,000 – 1.5M including platform setup, governance and enablement. A full 12-month transformation covering 3–5 departments typically runs MUR 4M – 10M depending on data complexity and integration scope. We always start with a fixed-fee discovery so the investment envelope is clear before commitment.
Do we have to use ChatGPT? What about data residency?
No. We deploy on Azure OpenAI in EU regions, AWS Bedrock in eu-west, Vertex AI in europe-west, or on-premise / sovereign Mistral and Llama deployments where regulators or contracts require it. Data residency is a design input from day one, not an afterthought.
How do AI agents differ from chatbots or RPA?
A chatbot answers questions. An RPA bot replays clicks. An AI agent has a goal, picks tools, gathers information, takes actions in your systems, observes the result and tries again if it fails. Agents replace whole sub-processes — not single tasks. We help you decide which technique fits each use case.
How do you handle bias, hallucination and AI safety?
Every AI system we ship has a documented Algorithmic Impact Assessment, an evaluation harness with quality and safety tests, retrieval-augmented grounding where appropriate, human-in-the-loop on high-impact decisions, prompt-injection and jailbreak red-teaming, and continuous monitoring. This is the controls layer of ISO/IEC 42001 in practice.
Can you integrate AI with our existing systems — SAP, Oracle, Microsoft 365, Salesforce?
Yes — and most of our work is on the integration boundary. We connect through APIs, webhooks, message queues, Microsoft Graph, OData, custom connectors and even RPA where systems have no programmatic surface. Every integration is logged, monitored and auditable.
How fast can we see results?
A scoped pilot typically reaches production in 8–12 weeks. The first measurable impact (time saved, errors reduced, response time improved) usually shows up in week 4–6 of the pilot. Full transformation across multiple departments is a 12–24 month programme delivered in waves.
Do you only serve large enterprises?
No. We have dedicated packages for SMEs that need automation and AI without enterprise pricing — typically a fixed-fee 8-week build on n8n + Azure OpenAI / Claude, covering one critical department. SMEs are how most Mauritian AI transformations should start.
$ ai.transformation --book
From a single AI use case to a full operating model — let us scope your AI transformation.