Clients

Trusted by demanding organisations.

Large accounts, mid-caps and firms with a strong identity: our clients share one requirement — measurable results.

Case studies

Major railway infrastructure manager — Solutions

Monitoring managed by the monitoring team, offering everyone tailored intelligence with no effort and no new tools to master.

Context and needs : Unevenly informed teams, losing a lot of time searching for useful information with mixed success, and little shared culture on cross-cutting innovative topics.

APAIA Watch
Monitoring

Architecture and engineering group — Consulting

A leadership team aligned on a clear, pragmatic AI roadmap.

What we did : Process mapping, use-case identification and prioritisation (image and text generation), make-or-buy and impact assessment, roadmap and a solutions monitoring unit.

Prioritisation
Roadmap

Engineering group — Solutions

Adding an AI-assisted virtual data room to a service delivered entirely by hand until now.

What “APAIA Make or buy Agent” brought : Segmentation of the players addressing this need. Detailed view of the players in each segment. Access to detailed data on the most relevant players to inform the make-or-buy decision.

Sourcing
Make or buy

Independent mutual insurer — Delivery

A sovereign agent that builds reports and ad hoc studies from raw unit-level data.

Context and needs : Heavy time loss consolidating data, limiting high-value ad hoc studies: pricing adjustments, loss-making contracts, trend anticipation, compliance. Personal data and strong regulatory-compliance stakes.

Sovereign
Agent

Major design group — Delivery

Bringing AI into the creative process to expand each designer’s creative potential and make team creation easier.

Context and needs : An individualised creative process, from sources of inspiration to representations. Highly differentiating proprietary data, hosted on a private platform.

Sovereign
Creativity

Major engineering group — Consulting

Balanced governance between IT and business units to deploy AI.

Context and needs : Multiple uncoordinated initiatives, fast-growing shadow IT, little visibility on priorities and stakes at executive-committee level.

Organisation
Governance

Mid-cap food manufacturer — Delivery

An agent that reads, compares and spots anomalies across the whole technical documentation of products.

Context and needs : Constantly changing technical product documentation, with a heavy update process that is costly to keep accurate. Source data hosted in the company’s IS (PLM, ERP, QMS), and also shared with third parties.

Quality
Productivity

Where does your organisation stand on AI?

A maturity assessment across 5 criteria and 9 sub-criteria, run through guided interviews. You leave with a clear view of where to improve.

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