We know AI matters, but not where to start.
You want a short list of use cases, ranked by value and feasibility, before spending on tools.
AI that does real work, under human control.
Most companies have tried AI tools. Few have put AI into a process that runs every day, with results they can measure. We identify where AI pays off in your operations, choose or build the right solution, put it into production with oversight and an audit trail, and train your teams to use it.
For
Companies of every size that want AI in their daily operations, from SMEs to banks.
You get
A ranked use-case map, a build-or-buy decision, a first use case in production, and trained teams.
How we work together
A milestone-based mandate, from diagnostic to production.
You are probably asking one of these.
AI projects usually start from one of these four places.
Our teams lose hours to repetitive work.
Reconciliation, document review, reporting, customer requests, onboarding checks: work an AI agent can prepare and a person can approve.
Our pilot never reached production.
The demo worked. Data access, controls, and ownership did not. The project needs an operating model, not another prototype.
Compliance has to sign off.
Regulated or sensitive work needs approval points, logs, and clear limits, designed in from the start.
Where AI pays off.
Examples of what we put into production. The method is the same in every sector; the use cases come from your own processes.
Finance and treasury
- Bank reconciliation and matching
- Cash forecasting
- Exposure and limit monitoring
Compliance and risk
- KYC and onboarding file review
- Alert triage for transaction monitoring
- Regulatory watch and summaries
Operations
- Invoice, contract, and document extraction
- Demand forecasting and stock planning
- Scheduling and reporting
Customer service
- Request triage and routing
- Draft answers for agent approval
- Knowledge base upkeep
Sales and marketing
- Market and competitor analysis
- Content drafting and editorial calendars
- CRM updates
Teams and knowledge
- Internal search across documents
- Drafting, translation, and summaries
- Training on AI tools
What we do.
Five workstreams that take AI from idea to daily use.
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Map processes and data, and identify deploy-ready use cases.
We review how work flows through your teams and where the data lives, then rank use cases by value, feasibility, and risk.
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Choose the approach: buy, adapt, or build.
For each use case we compare off-the-shelf tools, configured platforms, and custom agents on cost, data protection, and dependence on a single vendor.
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Design human-in-the-loop oversight.
We decide what the AI prepares, what a person approves, and what happens when the AI is unsure.
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Define guardrails, escalation paths, and audit trails.
Access rights, limits, logs, and the records GDPR and the EU AI Act call for.
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Stage the rollout from pilot to production, and train your teams.
A first use case live on real work, measured against a baseline, then extended. Your people learn to use the system and to check its work.
What you get.
Each phase ends with something you can use, not a slide deck.
AI diagnostic
Your processes and data reviewed, with use cases ranked by value, feasibility, and risk.
Solution choice memo
Buy, adapt, or build for each priority use case, with costs and a data-protection review.
Oversight and control design
Approval points, escalation paths, access rights, and the audit trail.
A use case in production
Running on real work and measured against the baseline agreed at the start.
Compliance records
Purpose, data, risks, and controls of each system, documented with GDPR and the EU AI Act in mind.
Team training
Hands-on sessions so your people use the tools, check their output, and improve them.
How it runs.
Four phases. Each ends with a decision, so you never commit to the next one blind.
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Phase 01
Diagnose.
Processes, data, and teams reviewed. Use cases identified and ranked.
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Phase 02
Choose.
Buy, adapt, or build, decided use case by use case, with costs and risks on the table.
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Phase 03
Deploy.
A first use case in production, with oversight, guardrails, and an audit trail.
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Phase 04
Adopt and measure.
Teams trained, results measured against the baseline, next use cases planned.
Financing in France
Your AI project can be financed.
French companies with up to 49 employees and more than three years of activity can finance an AI integration project with Bpifrance's Prêt Boost Intelligence Artificielle, an unsecured loan for AI adoption: automation, predictive analytics, content generation, and team training.
The loan is granted by Bpifrance to your company, and the application goes through your chartered accountant. We provide the scoped project description and budget that support it.
tracee is an independent provider and is not affiliated with Bpifrance. Loan terms are set by Bpifrance and may change; check the current conditions on its site.
See the Prêt Boost IA on Bpifrance€5,000 to €100,000
Loan amount.
Up to 49 employees
Company created more than three years ago.
No guarantee
No personal or company guarantee required.
3 to 5 years
Repayment term, with up to 12 months before the first repayment.
Why tracee.
Patent
Multi-agent AI architecture.
Patent in advanced review covering a multi-agent AI architecture for digital-payment platforms: automated transaction flows, stronger security, and contextual execution.
Current mandate
AI and payments for a UN fund.
Advising a UN multilateral climate fund on digital payment and AI infrastructure across six Central African countries.
Independent
No software to sell.
tracee does not sell software and takes no referral fees, so the tool we recommend is the one that fits your data, budget, and constraints.
Frequently asked
Common questions about AI integration.
What is an agentic AI workflow?
A process in which an AI agent carries out steps on its own, such as gathering documents, checking them, and drafting a decision, while a person approves the result at points you define. Unlike a chatbot, the agent works inside your tools, under rules you set.
Do you work with companies outside finance?
Yes. Our deepest experience is in regulated finance, where controls are strictest, and we apply the same method to any company that wants AI in its daily operations, from SMEs to large groups.
Which AI tools do you use?
We are independent: no software to sell, no referral fees. We recommend what fits your data, budget, and constraints, whether an off-the-shelf tool, a configured platform, or a custom agent built on a leading model.
How do you handle data protection?
It is part of the design: where data is processed, who can access it, what the model is allowed to see, and what is logged. We prepare the records GDPR requires and map your obligations under the EU AI Act.
Can our AI project be financed?
In France, companies with up to 49 employees and more than three years of activity can apply for Bpifrance's Prêt Boost IA, from €5,000 to €100,000, without guarantee. We provide the scoped project description and budget for the application.
Our other services.
Most engagements combine services, because the decisions are connected. Each one runs under one of our four engagement formats.
Start with a conversation.
Thirty minutes, no slide deck, no obligation. Tell us which work you want AI to take on, and we will tell you whether we can help.