AI for business processes.
AI agents and automation: from use case to production, then to real use.
Atlassian Platinum Solution Partner · Alongside IT departments since 2008 · Paris and Lyon
An agent does not just answer.
A process has been identified. The potential gains are understood. What remains is turning the idea into something that actually works. We design and implement AI solutions that can automate or augment certain steps of a business process, in particular through agents connected to the information system where that is relevant.
A large part of the work done in businesses consists of searching for information, analysing documents, producing summaries, checking data, answering requests, feeding systems or triggering actions.
An AI agent can be given a goal, search for information, use tools and carry out a sequence of actions. That is what sets it apart from a simple conversational assistant.
What AI can take on.
Our five-stage approach.
We support the whole cycle, from analysing the process through to running it over time. Adoption is prepared from the scoping stage and measured after go-live.
Analyse the existing process, its volumes, its irritants, its costs, the edge cases and the expectations of the teams who run it today.
Define the agent's scope, the value expected, the applications and data involved, the human control rules and the success criteria.
Design, build, connect, test and then release a first version on a controlled scope.
Explain the new roles, train the users, organise the handover between agent and human, and track usage indicators.
Measure the real gains, handle errors and edge cases, develop the agent and organise its maintenance, either with you or at BleuLemon.
From assistance to automation.
The aim is not necessarily to reach the last stage. The right level depends on the value expected, the reliability achievable and the risk attached to the process.
Going live is only the beginning.
An AI agent only creates value if the teams adopt it and it is fully built into the way they work.
We support people in getting to grips with it, define the new roles and the handover rules between human and agent, then measure its adoption and the gains actually achieved.
Making the AI agent a genuine digital colleague, useful, integrated and able to evolve with the needs of the business.
Frequently asked questions
A question that finds no answer here is dealt with in a thirty-minute conversation, about your actual context rather than a general case.
Talk to an expertDo you need to go through the AI Assessment first?
No. If the use case is already identified, the sponsor appointed and the process well enough understood, we can go straight to implementation. Otherwise, the AI Assessment is there to bring it out.
What is the difference between an AI agent and a chatbot?
A conversational assistant mainly answers a question. An agent can act: consult several systems, take on different steps and trigger actions.
How do you keep human control?
For each use, we define what the agent can carry out on its own, what has to be checked after execution and what requires prior validation. The more sensitive or the harder to undo the action, the stronger the human control has to be. That is the subject of the AI governance.
What if the agent gets it wrong?
Risk is dealt with from the design stage: scope, data, tests, rules, rights and thresholds for handing over to a human. Access rights limit what the agent can do; they do not guarantee that what it produces is correct.
Who maintains the agents after the project?
Your teams, once the skills have been transferred, or BleuLemon under a maintenance and development arrangement.
Going further: The Artificial intelligence overview·AI assessment & roadmap·AI skills for IT teams·AI governance