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AI offer — Operations & Product

Put AI to work.
Not just your teams.

We turn artificial intelligence into operational solutions: automation of your business processes with human supervision, and AI products built by senior teams. Fewer manual tasks, measured results.

Let's talk about your project Explore our solutions
  • Measured results
  • Dedicated experts
  • From design to operations

Two ways to take action

Two ways to put AI to work.

Offer 1 — Operations

Hand your repetitive tasks over to AI.

We design, deploy and supervise AI agents able to take over your business processes end to end.

  • Fewer manual tasks, faster operations
  • Experts who supervise the exceptions
  • A precise scope — one process at a time
  • Clear tracking of costs, quality and results
Identify a process to automate

Offer 2 — Product

From your idea to a product that works.

We assemble the team of experts needed to design, build and take your AI product to production.

  • A senior team matched to your project
  • A product designed around your users
  • Integration with your tools and your data
  • Support through launch and beyond
Discuss my AI product

Example use cases

Tangible gains, process by process.

Document management

Automatically extract, verify and organise your invoices, contracts and other documents.

up to −70%processing time

Customer service

Handle routine requests, prepare responses and escalate complex cases.

up to −60%manual tickets

Sales operations

Qualify inbound requests, enrich the CRM and automate follow-ups.

up to +40%qualified leads

Back office

Streamline approvals, reporting and administrative coordination.

up to −50%admin time

Orders of magnitude observed on comparable setups — your quantified targets are set together during scoping, then measured during the pilot.

A simple, effective process

A measured pilot before any industrialisation.

1

We identify the opportunity

A 2-week scoping phase: we analyse your processes, your goals and the potential gains, with quantified success criteria — cost per operation, error rate, turnaround times.

2

We deploy a first solution

A 2-to-4-month pilot in real conditions, on your data. Every indicator is measured and shared: you see what the automation delivers, week after week.

3

We scale it up

When the results converge, we industrialise, supervise and improve the solution with your teams, with a skills handover. Otherwise, the scope is adjusted — you never invest on a promise.

Experts from the network,
not a black box.

Behind every setup, a short, senior team from the Hub: the AI agents execute, the humans frame, supervise and answer for the quality.

Steering

AI Product Owner

  • Frames the use case and the expected outcome
  • Drives the backlog and the AI metrics (quality, cost, business value)
  • A product-builder profile, not a ticket manager

Build

AI Engineer

  • Designs the architecture: LLM, RAG, agents, integrations
  • Develops, evaluates and industrialises the models
  • Guarantees robustness, security and controlled costs

Data

Data Engineer

  • Prepares and consolidates the data
  • Sets up the pipelines and monitoring
  • An AI system is only as good as its data

Adoption

Designer & change

  • Designs genuinely useful AI interfaces
  • Trains your teams and organises the upskilling
  • Anchors the tool in the real workflows of the business

The market has tipped.

2/3

of companies already use generative AI

But usage remains mostly experimental, with productivity gains still limited.

Banque de France, 2026 survey
+60%

growth in demand for "AI agents" skills in one year

Profiles able to orchestrate AI agents are the most sought-after on the French market.

Malt Tech Trends 2026
No. 2

AI, the second most requested freelance skill

22% of mission requests — even non-technical ones — now require AI expertise.

Malt Tech Trends 2026

Why digitags?

The right experts. The right technology. Someone truly accountable for the result.

We bring together business expertise, technology talent and operational support to turn your ideas into solutions people actually use. Not just consulting. The real thing.

Let's discuss your project
Business expertise

Senior profiles from the network, with field experience.

State-of-the-art technology

AI agents, automations, tailor-made integrations — with no lock-in to a closed ecosystem.

Operational support

From rollout to results tracking, with a skills handover.

Guardrails from day one

Human supervision, audit log, GDPR & AI Act compliance. Your data stays with you.

Frequently asked questions

Everything about AI in production.

Which business processes lend themselves to AI automation?
Frequent, repetitive, documented processes: document handling, back office, first-level support, vendor coordination, data qualification. A good candidate has volume, rules you can express, and exceptions you can identify. The scoping phase exists precisely to verify that potential before you invest.
Does the AI work on its own?
No. Every setup combines AI agents with human supervision: the AI executes within a restricted decision scope, our experts handle the ambiguous cases, and every action is traced in an audit log. That's what makes the automation reliable — and compliant.
What happens to my in-house team?
It levels up. The goal is not to replace your people but to take the repetitive work off their plate: we train them, document the setup and organise the handover so the value stays with you.
Why run a pilot rather than deploy directly?
Because an AI setup is judged on measurements, not on a demo. The pilot in real conditions establishes the cost per operation, the error rate and the turnaround times on your data — and the decision to industrialise is made on those numbers.
How is GDPR and AI Act compliance ensured?
From the scoping phase: data mapping, a documented decision scope for the AI, human supervision, an audit log and controlled hosting. Your data stays with you and we favour agnostic tools, with no lock-in to a closed ecosystem.

A process to automate,
an AI product to build?

Tell us what you need: we'll frame the scope
and the success criteria together.

Scope my AI project