AI for teams
Cut the time spent searching, writing, checking, documenting or producing.
- Knowledge base
- Internal support
- Software development
- Training & adoption
Surface the right AI use cases. Take them all the way to production.
Studio Machina supports companies end to end: identify the right AI use cases, integrate them into your existing tools and measure the results.
Book a callWe had prototypes that worked in a demo. Studio Machina put them into production without us losing control. The investment paid for itself in under six months, and our teams now handle 30% more cases at constant headcount.
Technologies that make the difference
Companies aren't short of AI ideas. They're short of a clear path to real usage.
An AI use case only creates value when it's chosen with the teams, connected to the right tools, secured, adopted and measured over time.
Wrong use cases
Topics chosen without real impact, or too complex to implement.
Insufficient integration
AI disconnected from existing data, tools and processes.
Weak adoption
A solution delivered, but rarely used by teams day to day.
From idea to a useful AI service.
Studio Machina supports companies across the whole value chain: surfacing the right use cases, choosing priorities, deploying useful solutions, training teams and measuring results.
- 01
Identify
Workshops with teams, analysis of pain points, exploration of AI opportunities.
- 02
Prioritise
Selecting use cases by impact, feasibility, risk and adoption.
- 03
Deploy
AI solutions integrated into existing tools, with access rights, traceability and oversight.
- 04
Adopt
Training, team support, usage measurement and continuous improvement.
Concrete AI use cases, integrated into your operations.
Three broad families of use cases.
AI for business processes
Connect AI to documents, operations and existing tools.
- Tenders & RFPs
- Document management
- Business copilots
- Specialised agents
AI in products and customer experience
Embed AI into existing products and services to improve the experience or create new uses.
- Customer experience
- Personalisation
- Customer journeys
- Augmented services
End-to-end support, in three steps.
A path tailored to your maturity. We start at the most useful step: scope, deploy or scale.
01
Explore & prioritise
AI scoping
Identify the right AI use cases and choose priorities.
Includes
- Workshops with business and IT teams
- Use-case qualification
- Impact / feasibility / risk scoring
- Execution roadmap and budget estimate
02
Build & integrate
AI deployment
Turn a priority use case into a service your teams can actually use.
Includes
- Functional and technical design
- Integration with existing tools and data
- Business copilot, specialised agent or automation
- Access, traceability, training and production rollout
03
Scale & sustain
Run & Adoption
Sustain, measure and scale the first use cases.
Includes
- Usage / cost / quality monitoring
- Continuous improvement
- Training of internal champions
- Extension to other teams and new uses
Une seule trajectoire, un seul interlocuteur responsable. We don't sell days; we deliver a bounded outcome: clear scope, defined deliverables, measurable adoption.
A single point of contact, an ecosystem of experts.
Studio Machina runs missions with a senior point of contact accountable for the result, while mobilising an ecosystem of experts as needed: AI consultants, AI developers, trainers, cloud, DevOps, security, data and IT-integration experts.
Clients get a simple relationship with a single owner, without giving up the depth of a specialised collective.
AI services already in production.
Two first references, genuinely in use, on a foundation that's reusable from one case to the next. Technical detail remains available to your technical teams.
Energy
Automatically triaging recurring network alerts.
Triage of the network operations centre's (NOC) most frequent alerts — up to 80–90% of the recurring workload — is automated by AI agents, with human control over sensitive cases.
Why it matters: teams save time on a recurring flow without losing control over sensitive incidents.
Read the case study
WealthTech · Wealth-management software
Industrialising agentic AI across engineering.
A shared agentic-AI practice, deployed across more than 20 engineering teams — from AI-assisted coding to vulnerability remediation — with common standards.
Why it matters: AI doesn't stay confined to a pilot team; it becomes a shared, governed and repeatable practice.
Read the case studyWhat decision-makers ask us.
A few answers to frame a first conversation.
What is Studio Machina?
An AI integration firm that helps companies take their AI use cases from concept to an operational service. You get a single senior point of contact, accountable for the result, backed by an ecosystem of experts: AI consultants and developers, IT integration, cloud, DevOps, security, data and training.
Who do you work with?
Mid-market companies and large accounts that want to industrialise AI. Our natural counterparts are CIOs, CTOs, executive, product and business leadership.
How are you different from an IT services company, a freelancer or a strategy firm?
We sell neither days nor slides. We deliver a bounded outcome, with an accountable senior lead and an ecosystem of experts mobilised as needed. And we go all the way to production: every mission also lays a reusable foundation, so the next project plugs in faster than the last.
Do you only work on AWS?
AWS is where we excel and we're an Anthropic partner. But we start from the client's real environment. Our role is to integrate AI into your information system, not to impose a technology.
Does it fit if we already have a cloud, data or AI team?
Yes. In that case we come in to accelerate: we help scope, prioritise, secure and deliver in collaboration with your internal teams.
How does a mission start?
Most often with a short scoping: objectives, use cases, available data, security constraints, existing architecture, risks, expected value and roadmap. It lets you decide what to build, in what order and with what investment.
How do you measure success?
With simple indicators defined from the start: real usage, time saved, quality, reduced risk, controlled costs and repeatability. AI that nobody uses isn't a success.
Want to identify the right AI use cases for your company?
In 30 minutes, we qualify your priorities, identify the first realistic use cases and define a simple path to measurable value. Describe your context in a few lines.