The firm

AI is only worth as much as the data you give it.

LinkTec is an AI & data consulting firm born from research and built for production. The useful question in 2026 is not which model to choose, but how to make an SME's data usable, contextual and secure.

What led to this firm

Not an agency pivot: one continuous technical trajectory, from academic research to the operational ground of SMEs.

  1. 01

    University education in AI in progress (Bachelor AI & Data)

    Theoretical foundations, applied mathematics and machine learning — the base that makes it possible to choose an architecture instead of following a trend.

  2. 02

    Research laboratories in robotics and AI

    Experience in research laboratories in robotics and artificial intelligence — internships and academic projects. Rigorous modeling, experimental validation, documented choices: the method that still structures every engagement.

  3. 03

    2025 — LinkTec is founded

    The firm was created to close one precise gap: AI is demonstrated everywhere, yet almost never connected to the real data of the companies that actually work.

  4. 04

    Three branches, one expertise

    Modules for local businesses, Studio for structured SMEs, Labs for strategic AI stakes — the same expertise, distributed according to company maturity.

  5. 05

    Studio — BETA by application

    The SaaS operating base opened to the first 50 SMEs, by application, so it faces real usage before being sold.

  6. 06

    2026 — Labs & AI-Ready Audit

    The AI-Ready audit becomes the signature product of Labs: measure maturity, scope the data layer, quantify priorities before writing a single line of code.

Why now? Models have become accessible to every company; the data layer that makes them useful still has to be built in nearly every SME. That is exactly what this firm does.

Built as a firm, not as an agency

The difference is not a slogan: it shows in what is sold, in what is delivered, and in what remains once delivery is over.

An agency LinkTec

Sells hours.

Commits to a scope and a measurable outcome.

Starts from communication.

Starts from the data: what the company has, where, in what state.

Delivers, then moves on to the next project.

Audits, builds, then stays to keep the system running.

Keeps its technical choices to itself.

Makes its architecture choices explicit and delivers documented, transferable code.

Three rules, held on every engagement

Data first

No AI deployment before knowing what the company has, where it lives, and in what state.

Built for production

A system designed to hold real load, not a demo built to impress.

Academic method, operational delivery

Modeling, validation, documentation — applied to SME cases, not to publications.

A research-driven approach, applied to SME ground

The work published by LinkTec Labs is not a showcase: these are the method building blocks actually used on engagements. One technical note is online, other topics are under review — each will be published once its sources have been verified.

It is also the rule that protects the client: what is not demonstrated is not sold.

How are Labs engagements led?

Each Labs engagement is led by BN-LinkTec with a multidisciplinary research team assigned to the project. The work draws on university education in AI & Data currently in progress (Bachelor AI & Data), experience in robotics and AI research laboratories through internships and academic projects, and complementary skills in AI, data, digital twins, architecture and production delivery.

Responsibilities — scoping, research, architecture, production code, documentation and handover — are allocated according to the expertise required. Every contributor is bound by a contractual confidentiality obligation; their role and access scope are defined before participation, and access is limited to information strictly necessary for the engagement.

  • 1 business day Response time to any request
  • GDPR Compliance and least-privilege access
  • OVH FR Data hosted in Europe

One expertise, three ways in

Next step

Let's talk about your data layer

A conversation to understand your context, or twenty focused minutes to leave with a first recommendation.