Integrate AI.
Improve real work.

AI AGENTS & WORKFLOW AUTOMATION

AI agents
and automation.

Qualify a request, prepare a file, gather data or feed a tool. An automation follows planned steps; an AI agent can choose some steps depending on the context. The level of autonomy depends on the action.

• SituationsSorting incoming items, administrative preparation, operations follow-up, data synchronization.
• First deliverableOne defined flow, its connections and the exceptions to handle.
• To be agreedRead and write permissions, approvals, operation and follow-up.

ENTERPRISE SEARCH & RAG

An assistant connected
to your documents.

Find a procedure, compare files and prepare an answer with its sources. Retrieval-augmented generation combines document search with a generative model; it replaces neither access rights nor version management.

• SituationsKnowledge base, technical documentation, internal support, procedures.
• First deliverableAn authorized corpus and representative questions, including some whose answer is absent.
• To be agreedSource updates, permissions and criteria for an acceptable answer.

LOCAL AI & ON-PREMISE DEPLOYMENT

AI on your
infrastructure.

Install a local engine, connect the data and organize access. An application on a computer can still call a remote service: the real place of processing and the dependencies need to be checked.

• SituationsInternal documents, on-site use, stable tasks and a need to control certain dependencies.
• First deliverableOne model on the chosen hardware and one representative task to try.
• To be agreedCapacity, license, network, backups, updates and maintenance.

MODEL CUSTOMIZATION & FINE-TUNING

Models
adapted to your business.

Improve an output format, a classification or a targeted behavior. Adaptation can go through instructions, tools, RAG or training on examples. The choice depends on what needs to change.

• SituationsVariable documents, business categories, repetitive writing or a specialized task.
• First deliverableA baseline for comparison and a small set of representative cases.
• To be agreedUsable data, examples held out from training, license and upkeep cost.

EMBEDDED AI ENGINEERING

An integration
within your environment.

Observe the work on site or remotely, understand the tools and build with the team. An approach close to forward deployed engineering: engineering steps in where the need and the constraints meet.

• SituationsCross-functional project, tool to connect, moving from prototype to shared use.
• First deliverableOne complete end-to-end flow within an agreed scope, with acceptance criteria.
• To be agreedInterventions, access, roles, pace and handover of the integration.

AI ADOPTION & ENABLEMENT

Supporting
your team’s use of AI.

Start from tasks, not from a list of prompts. Use ChatGPT, Claude or a local tool to prepare deliverables, structure the context and know what needs to be reviewed.

• SituationsUnder-used licenses, individual experiments that are hard to share, choice of tools.
• First deliverableOne business exercise, a reusable method and examples of the expected result.
• To be agreedAudience, exercise data, available tools and getting-started goals.