gensai.aiGensai designs custom AI agents that act inside your processes: answer a request and book an appointment, read and analyse documents, produce reports, trigger actions in your tools. Agents that are autonomous within their scope, hosted in France or in Europe, framed by guardrails and supervised by your teams.
Where a chatbot talks, an agent acts: it reasons, picks its tools, queries your databases, carries out actions and checks the result. Booking an appointment and writing it into the calendar, reading a file and extracting its key information, producing a periodic report: tasks an agent handles end to end.
Gensai builds these agents to measure, with proven orchestration components and low-code tools to validate a first use case, connecting them to your business tools through standard protocols such as MCP: CRM, calendars, messaging, databases. This agentic AI fits into your existing processes, it does not replace them.
Autonomy comes in doses: a guided assistant, a framed workflow or an autonomous agent, each process has its right level. Every agent ships with its guardrails: minimal access rights, an explicit list of allowed actions, full logging and human validation on sensitive operations. And sovereignty is decided at the architecture stage: open models, hosting in France or in Europe, on your servers if required.
Use cases for autonomous agents
Appointment booking
An agent picks up or reads the request, understands the need, checks the calendar and confirms the appointment, in real time.
High-volume document analysis
Files, supporting documents, contracts: automated reading, extraction of key information and summarisation.
Automated reporting
Periodic reports produced from your business data, in your teams' format, without manual work.
Booking management
Confirmations, changes, reminders: the requests of a hotel, a restaurant or a visitor site handled on every channel.
Event logistics
Registrations, badges, reminders, attendance lists: the repetitive tasks of a trade show or congress orchestrated automatically.
Group and school requests
Qualifying requests, scheduling visit slots, tracking files: a smoother cultural back office.
Donations and memberships follow-up
Personalised reminders, receipts, reports: a non-profit's admin handled without late evenings.
Call quality control
Transcription and analysis of phone recordings: compliance of exchanges, anomaly detection, dashboards.
Our references
Frequently asked questions
What is an AI agent?
An AI agent is a system able to reason, decide and act to reach a goal: it analyses a request, breaks it into steps, picks its tools and carries out actions on your systems (CRM, calendar, database). Where a chatbot answers, the agent acts.
What is agentic AI?
Agentic AI refers to systems where one or several AI agents reason, plan and act to reach a goal, relying on tools (search, databases, business applications). A single agent handles one task, an orchestration of agents chains several steps with distinct roles, always under human supervision.
What is the difference between a chatbot and an AI agent?
The chatbot converses and informs. The agent executes. An intelligent answering service that understands the request, checks availability and records the appointment in the calendar is an agent: the conversation is only its interface.
How do you keep control over an agent?
Through guardrails: minimal access rights, an explicit list of allowed actions, logging of every operation and human validation on sensitive steps. Gensai chooses with you the right level of autonomy for each process.
Can an AI agent be sovereign?
Yes. A sovereign agent relies on open models and runs with a French or European hosting provider, or on your servers. Your data never leaves the chosen perimeter and is never used to train third-party models. Gensai designs its agents this way from the architecture stage.
Which processes should be automated first?
Repetitive, time-consuming and well-defined tasks: appointment booking, sorting and analysing documents, producing recurring reports. A use-case identification workshop helps prioritise by value and feasibility.
Can an AI agent work with my existing tools?
Yes, that is its very purpose. The agent connects to your CRM, your calendar, your messaging or your database through their APIs or standard protocols such as MCP, with rights limited to what it has to do. It fits into your tools, it does not replace them.
How long does it take to put an AI agent into production?
A first use case on a well-defined process usually takes 2 to 3 weeks, the time to connect the tools and test the agent on real situations. Going into production then takes 1 to 3 months, depending on the integrations and the level of human validation required.
A process to automate?
Describe the task that keeps your teams busy: Gensai identifies the right level of autonomy and builds the agent that takes care of it.