Methodology

A twenty-year method, instrumented by AI

Complex projects rarely fail for lack of technical talent: they fail for lack of method. Ours has not changed its principles in twenty years - scope before acting, document every trade-off, ship in validated stages. What changed is the tooling: code review, regression detection, compliance and security checks are now instrumented at every phase. AI does not replace the architect, it removes the mechanical work.

Structured phases

100%

Documented decisions

Surprises in production

20+

Years of experience

Methodology

Why methodology makes the difference

70% of digital projects exceed their budget or timeline. The cause? Rarely technology. Almost always the lack of framing, absence of documented decisions, and improvisation.

Our methodology eliminates these risks by structuring each phase with concrete deliverables, validation checkpoints, and complete traceability.

Seniors only

Every expert in the network has twenty years or more behind them. The person who scopes your project is the one who ships it: no cascade, no subcontracting.

Delivery instrumented by AI

Code review, regression detection, compliance and security checks are tooled at every phase. AI does not replace the architect: it removes the mechanical work.

Full traceability

Every decision is documented as an ADR, every prompt and configuration versioned like code. You can reconstruct any choice six months later.

We stay through the run

Agentic workflow supervision, observability, quality and security steered after go-live. A project delivered then abandoned is not a project delivered.

The 5 phases

From first exchange to production

Every phase ends with concrete deliverables and a validation point. Nothing moves without your agreement - and the AI tooling runs at every stage, not only at the start.

Scoping & Diagnostic

2 to 4 weeks

Understand before acting

Why it's crucial: An architect with twenty years behind them sees in three weeks what a junior team takes six months to discover. AI tooling reads the entire codebase and IS landscape in the meantime: it does not replace the diagnostic, it removes its blind spots.

What we do

Audit of existing systems (architecture, code, infrastructure, processes)
AI-tooled analysis across the whole repository, not a sample
Mapping of the IS and its integration points (APIs, data, events)
Identification of constraints and technical debt
Business needs and user journey analysis
Documented technical and functional trade-offs

Deliverables

Audit report
Technical and IS map
Structured roadmap
Decision matrix

Architecture & Design

2 to 3 weeks

Lay solid foundations

Why it's crucial: Wiring an agent into an information system is not a tooling question, it is an architecture question: which accesses, which guardrails, which traceability. This is where it is decided whether your AI stays a demo or holds up in production.

What we do

Agentic architecture design: agents, orchestration, guardrails, error recovery
Design of RAG chains and MCP connectors into your business domains
Stack choices: BFF, microservices, API contracts, data model
Pattern definition (API, data, events, cache, observability)
Prototyping and proof of concept where the risk justifies it
Review and validation with your teams

Deliverables

Architecture document
Technical diagrams
ADR (Architecture Decision Records)
Validated POC

Build & Integration

8 to 16 weeks

Build with rigour

Why it's crucial: Code quality determines future speed. Every commit goes through tooled review and then an architect: AI flags, a human decides. Agentic chains are evaluated like code - with test sets and regression checks on the answers themselves.

What we do

Iterative development in sprints
Development of MCP servers specific to your business domains
Systematic code review, AI-assisted then architect-validated
Continuous evaluation of agentic chains (test sets, answer regression)
Automated tests (unit, integration, E2E) and continuous integration
Embedded technical documentation, incremental deliveries

Deliverables

Reviewed and tested code
MCP servers and domain connectors
CI/CD pipeline
Incremental releases

Delivery & Go-live

1 to 2 weeks

Ship with confidence

Why it's crucial: A poorly prepared go-live is a major business risk - and since the AI Act, a regulatory one. Security, compliance and the fallback plan are verified before the switch, not discovered after it.

What we do

Deployment strategy (blue-green, canary, rolling)
Security and compliance checks (AI Act, data, agent permissions) before go-live
Environment configuration (staging, production)
Load and resilience testing
Documented rollback plan
Monitoring and alerting in place before go-live

Deliverables

Configured environments
Operational runbook
Compliance file
Active monitoring

Run & Optimisation

Ongoing

Operate and improve

Why it's crucial: An agentic workflow drifts: the data changes, the models change, the costs slip. We supervise ours in run - cost per request, failure rate, answer quality - and we carry the Ops and infrastructure expertise behind it.

What we do

Supervision of agentic workflows (cost per request, drift, failure rate)
Full observability (logs, metrics, traces)
Ops and infrastructure expertise provided continuously
Incident management and post-mortems
Continuous performance optimisation
Cloud FinOps and AI FinOps

Deliverables

Observability dashboards
Defined SLA/SLO
Cost and performance reports
Evolution plan

Case Studies

This methodology in action

Discover how our process translates into concrete results on real projects: e-commerce redesigns, cloud migrations, AI deployments.

View our case studies

Next step

Let's transform your digital project together

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