AI agents connected to your tools
Agents that query your applications, prepare actions and carry them out within authorized limits, with human validation where needed. See AI agents and chatbots.
AI · Team in Madagascar
AI Team in Madagascar: AI Agents and AI Features Built Offshore
At Etixio, an AI team in Madagascar designs and develops your AI agents, document search systems (RAG) and the AI features of your products, then takes them to production. The team is French-speaking, led by a tech lead and managed from France. It treats AI as software: with tests, evaluations, data security and cost tracking.
Who it’s for
SaaS vendors, SMBs, mid-sized companies and CIOs with AI use cases to deliver
What we build
AI agents, RAG, embedded AI features, POC takeover
Format
Dedicated team or fixed-price project
Leadership
Tech lead, managed from France
What we build
AI use cases built like software, all the way to production.
An AI prototype takes a few days to build. A reliable, secure service with controlled costs takes much more: integration with data and tools, evaluation sets, permissions management, monitoring and an update cycle. That is the work an AI team in Madagascar takes on, in your codebase and following your practices.
The team combines back-end and front-end developers, engineers specialized in model integration and QA profiles. It is supervised by a tech lead who owns the architecture and quality, and managed from France. To learn more about our teams there and how we are organized, see our Madagascar page.
Document search and RAG
Answers grounded in your documents and knowledge bases, with sources shown and access rights enforced. See RAG development.
AI features in your products
Embedded assistant, document extraction, summarization or classification, shipped as components of your software. See AI features for your product.
AI POC takeover
An existing prototype taken over, evaluated and completed (authentication, monitoring, error handling, costs) to become a production-ready service. See AI POC to production.
Who it’s for
When should you hand your AI projects to a team in Madagascar?
You have AI use cases, but no team to build them
The ideas are there, but your team is busy with the roadmap or lacks specialized profiles. The team delivers the AI use cases in parallel, without slowing everything else down.
Your POC is stuck before production
The demo was convincing, but security, answer quality and costs are not under control. What you need is engineering, not another prototype.
You want continuity on your AI features
Models, data and usage keep changing. A stable team retains knowledge of evaluations, prompts and architecture choices.
From work to deliverables
From use case to production release.
Choose the use case and define success
We start from your users’ tasks and define what the AI must produce, from which data, and how to measure that it is useful.
Build an evaluation set
Real examples and expected answers, validated with your business stakeholders, used to compare approaches and models.
Develop and integrate
AI service, connections to your data and tools, access rights, logs, tests and interface. The use case ships like the rest of your software.
Run and improve
Tracking of quality, errors and usage costs, evaluations rerun on every model or prompt change, improvements based on feedback.
What your team receives
- Code, tests and evaluation set
- Quality and cost tracking dashboard
- Technical and operations documentation
Models & tools
The technologies we use, depending on your use case.
The choice of model and architecture depends on the use case, the data and your confidentiality constraints. The team works with the main model providers as well as with self-hosted open models.
OpenAI, Claude, GeminiModels connected to your data and your screens.↗Mistral AIEuropean models, via API or self-hosted.↗LangChain & LangGraphOrchestration of agents and processing pipelines.↗MCP serversExposing your tools and data to AI agents.↗LLMOps & evaluationEvaluations, monitoring and cost tracking in production.↗Self-hosted open-source AIModels in your infrastructure, for sensitive data.↗
The choices that matter
Evaluation, data security and usage costs.
Evaluation. An AI feature without quality measurement degrades without anyone noticing. Each use case has an evaluation set rerun on every change, backed by tracking of feedback and errors in production.
Data security. Team access is role-based, development environments use test or anonymized data wherever possible, and transfers of personal data to Madagascar are framed by the safeguards provided for in the GDPR. For the most sensitive data, a self-hosted model can avoid sending content to a third-party provider. See also our AI precautions for businesses.
Costs. There are two costs to separate: the team, based on a monthly cost per person (see our rates), and running the AI, which depends on the model, the volume and the size of the content processed. We measure the latter from the prototype stage and optimize it by choosing the right model for each step.
Delivery in practice
AI solutions built by Etixio.
Etixio has built, among others, a RAG-based medical AI agent that gives anesthesia teams a chronological summary of the patient record, and Bobby, an assistant that gives natural-language access to ERP data.
How we work together
Start with a first use case.
Tell us about the use case, the data involved and your constraints. A first use case can be delivered as a fixed-price project, then continued by a development team in Madagascar that evolves your products and their AI features.
Frequently asked questions
AI team in Madagascar: your questions.
Can AI agents be developed offshore?
Yes, as long as the agent is treated as software, with evaluations, access rights, monitoring and technical leadership. At Etixio, the team in Madagascar is led by a tech lead, managed from France, and works in your code and tools.
Can our data be processed from Madagascar?
Yes, within a defined framework. Access is role-based, development uses test or anonymized data wherever possible, and transfers of personal data rely on GDPR safeguards such as standard contractual clauses. A self-hosted model is an option for sensitive data.
Which AI models do you use?
Models from OpenAI, Anthropic (Claude), Google (Gemini) and Mistral AI, as well as self-hosted open models. The choice is made on an evaluation set built with you, based on quality, cost and your confidentiality constraints.
How much does an AI team in Madagascar cost?
The team’s cost depends on the profiles, their seniority and headcount, based on a monthly cost per person. The cost of running the AI comes on top; we measure it from the prototype stage. See our offshore developer rates.
How do you measure the quality of an AI agent or feature?
With a reference set of examples validated by your business stakeholders, evaluations rerun on every model, prompt or data change, and production tracking of errors and user feedback.
How do you ensure delivery continuity?
Through organization: code, environments and evaluation sets in the cloud, redundant connections and workstations, backup power, the option to work remotely, handover with our teams in Mauritius, shared documentation and daily follow-up by the tech lead. See our Madagascar page.
Can you take over an existing AI POC?
Yes. We take over the code, data and model choices, build the missing evaluations, then add what production requires. See AI POC to production.
Which AI use case do you want in production?
Tell us about the use case, the data involved and your constraints. We will help you choose the first use case to build and the team to deliver it.