Business services
AI documentation assistant
Make a body of procedures and documentation searchable, with sources cited and access rights respected.
- Generative AI
- RAG
- Knowledge management
EXPERTISE
Artificial Intelligence & Automation
We work where AI genuinely changes a process: identifying use cases, prototyping, integrating with the information system, and industrialising.
THE PROBLEM
What we see on the ground
- 01
Prototypes never reach production
The demonstration convinces, then the subject stops: no business owner, no integration into the process, no one accountable for the answers.
- 02
The use case has no measurable value
The experiment starts from the technology that happens to be available. With no identified point of friction, the gain stays a claim.
- 03
The data is not ready
Scattered documents, incomplete reference data, inconsistent access rights: the quality of the answer is capped by the quality of what feeds it.
- 04
There is no control framework
Confidentiality, traceability of answers, error handling, accountability when a decision turns out wrong: as long as these are open, the use case stays confined to the pilot.
Turning AI into operational use and measurable gains.
- 01PROBLÈME
Strong pressure to “do AI”, scattered experiments, and no use genuinely embedded in operations.
- 02INTERVENTION AXENEO
We start from the processes: identifying and qualifying use cases, short prototypes, integration with business applications, then industrialisation and governance.
- 03RÉSULTAT
A prioritised portfolio of use cases, uses running in production and embedded in the business process, and a control framework that makes extending the scope possible.
What we do
Strategy & scoping
Choose few subjects, and choose them on criteria that hold.
- AI strategy and alignment with business priorities
- AI readiness: data, technical foundation, skills, governance
- Identifying and qualifying use cases
- Prioritisation by value, feasibility and risk
- Functional scoping and measurable success criteria
Generative AI & assistants
Uses anchored in the organisation's own documents and processes.
- Business assistants and internal copilots
- Knowledge search and retrieval (RAG)
- Document analysis and extraction
- Generating and rewriting operational content
- Decision support and information synthesis
Agents & automation
Automate sequences of work, not just answers.
- Tool-using AI agents and task orchestration
- Intelligent automation of business processes
- Automated handling of requests and incoming flows
- Integration with ERP, business applications and workflows
- Supervision and human hand-back
Industrialisation & governance
What separates a prototype from a service.
- From proof of concept to production: architecture, costs, operations
- Evaluating answer quality and building test sets
- Traceability, logging and error handling
- AI governance: permitted uses, data, accountabilities
- Compliance, confidentiality and access control
How we work
- 01
Identify
We start from the processes and from real points of friction. A use case with no business owner does not enter the portfolio.
- 02
Scope
Perimeter, data involved, success criteria, acceptable quality threshold and stopping conditions. Success is defined before the work starts.
- 03
Prototype
A short prototype, on real data, evaluated against a representative test set. The aim is to decide, not to convince.
- 04
Integrate
The use is plugged into the process and the existing applications. Without integration, adoption does not happen.
- 05
Industrialise
Operations, supervision, costs, scaling, version and model management. A use in production is a service.
- 06
Govern
A usage framework, quality control over time, traceability and accountabilities. That is what makes extending the scope possible.
USE CASES
Where we step in
Put a document estate to work
Make a corpus of procedures, contracts or technical documentation searchable, with sources cited and access rights respected.
Assist internal support
Qualify, route and pre-resolve recurring requests, keeping human hands on the sensitive cases.
Automate document processing
Extract data from an incoming flow, check it and load it into the business application, with exceptions handled properly.
Industrialise a proof of concept
Take a promising experiment and raise it to the standard of a service: quality, cost, operations, accountability.
Related case studies
Business services
Document processing automation
Automate the extraction, checking and integration of an incoming document flow, with a dedicated route for exceptions.
- Automation
- Document processing
- System integration
Business services
Internal service portal
Replace informal request channels with a single point of entry, approval workflows and traceability that can actually be used.
- Digital Workflows
- Service portal
- Automation
CONTACT
Let’s discuss your situation
We start from your process. A short conversation is enough to tell a use case that will hold in production from an experiment that will stop at the prototype.