1 to 2 weeks
AI framing workshop
We identify and prioritize the use cases that are genuinely profitable for your organization.
- Mapping of high-volume tasks
- Feasibility / value / risk assessment
- Costed roadmap
Solution by need
Integrate artificial intelligence where it truly changes the work.
No spectacular demo that leads nowhere. We start from your processes, pick a profitable use case, and ship it to production with guardrails and measured results.
The starting point
AI is only useful when wired to a real pain point.
We often meet the same signals before a first successful AI project. If two or more sound familiar, there is value to capture quickly.
- 01
Your teams retype the same information from one system to another.
- 02
The information exists, but nobody finds it fast enough.
- 03
AI experiments were run, but never reached production.
- 04
Management hesitates: privacy, cost and reliability remain unclear.
Use cases
Five families of use cases, one principle: deliver a verifiable result.
Read, extract and classify your documents
Invoices, contracts, forms, inspection reports: AI extracts the useful data, validates it against your rules and pushes it straight into your systems.
- Structured extraction with a confidence score per field
- Human review only on uncertain cases
- Full traceability document by document
Expected outcome
Hours of manual entry reduced to a few minutes of validation.
Maturity
Where do you stand today?
We adapt our support to your actual level. Most organizations we meet sit between the first and second step.
- 01
Exploration
Consumer tools used in scattered ways, with no framework or measurement.
- 02
First pilot
One targeted use case, measured, with a clear scope and budget.
- 03
Integration
AI is wired into your systems and part of daily processes.
- 04
Industrialization
Several use cases, supervised, governed and continuously improved.
Engagement formats
Three ways to start, depending on your starting point.
6 to 10 weeksMost chosen
Measurable pilot
One use case delivered to production, used by real teams, with tracked indicators.
- Integration with your data and tools
- Training for key users
- Before / after gain measurement
Ongoing
Industrialization
We extend AI to other processes and take care of supervision and governance.
- Cost and quality monitoring
- Usage policies and broader training
- Model and prompt evolution
Responsible AI
Trust is built before the first generated answer.
Every AI project we deliver meets the same requirements for privacy, traceability and human control - whatever its size.
Your data stays yours
Controlled hosting, no public model training on your content, per-client isolation.
Transparent answers
Cited sources, visible confidence levels and logging of sensitive exchanges.
Human in the loop
High-impact decisions remain validated by an identified, accountable person.
Québec compliance
Law 25, privacy requirements and internal policies taken into account.
Technical foundations
Mature building blocks, chosen for the need - never the other way around.
Models and orchestration
Azure OpenAIClaudeGeminiLLM open sourceOrchestration d'agents
Data and retrieval
PostgreSQLpgvectorRAGOCRPipelines ETL
Integration and monitoring
API RESTPower PlatformSupabaseJournalisationSuivi des coûts
FAQ
The questions we get before starting.
No. Most projects start with imperfect data. We pick a tolerant use case, clean what is required, and quality improves through use.
Next step
Let's pick your first profitable use case together.
Thirty minutes is enough to identify two or three concrete options and estimate the expected gain.