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Capabilities

Build the right product, then get it into production.

SaaS, business tools and AI features for teams moving from a business need to production.

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When this collaboration is useful.

I step in when a project needs product decisions and technical delivery to stay connected through a single point of contact.

  • An idea or business need must become a clearly scoped MVP.
  • An existing SaaS product needs stabilisation, a structured handover or further development.
  • An AI feature must serve a precise use case instead of adding a gimmick.
  • A product team needs an autonomous engineer who can stay through delivery.

End-to-end SaaS, MVP and digital product

Turn a business intent into a usable product without multiplying handoffs between scoping, architecture and engineering.

Starting point
You have a validated need, an initial product idea or an application that is no longer moving at the expected pace.
Problem to solve
The scope is still unclear, priorities compete or technical delivery lacks continuity.
Scope
User and outcome clarification, prioritisation, user journeys, architecture, full-stack engineering, APIs, deployment and iteration.
What you receive
A release scope, explicit trade-offs, a product delivered in stages and the foundation needed to maintain and evolve it.
How we start
A conversation about context, users, constraints and what must change in practical terms.
Expected outcome
An operational version proportionate to the need, with enough clarity to decide what comes next from real evidence.
See the Log²EU product scope

Useful AI in a product or business process

Embed AI where it improves a decision, a search or a workflow step, while keeping results understandable to the user.

Starting point
You have documents, data or a business workflow that requires too much reading, matching or manual processing.
Problem to solve
The AI use case is still abstract, disconnected from the product or difficult to evaluate from a business perspective.
Scope
Use-case framing, data-flow preparation, product integration, user experience, quality criteria, cost and limits.
What you receive
A focused prototype or an integrated feature, test scenarios and a clear view of what the system can and cannot do.
How we start
Real examples, the expected outcome and data constraints are enough to identify a first testable scope.
Expected outcome
An AI capability connected to daily work whose usefulness can be observed without exposing the business or promising full automation.
See applied AI in Log²EU

The scope can start smaller.

These engagements complement the two primary offers and can resolve one blocker before a broader build.

Automation

Reduce repetitive steps in an existing workflow without making its behaviour opaque.

Mobile applications

Bring a use case to mobile when its context, frequency or field usage makes that worthwhile.

Business tools

Structure data, roles and operations in an interface designed for day-to-day work.

APIs and integrations

Connect services, products and data with explicit responsibilities and error handling.

Handover and iteration

Understand the existing product, secure priorities and prepare a practical path forward.

Audit, prototype or product sprint

Answer a precise question before committing to a broader implementation.

A concise process with clear decisions.

The level of documentation and process changes with the project. The four responsibilities remain constant.

  1. Clarify

    Align the context, users, constraints and the outcome that matters.

  2. Decide

    Choose the scope, the risks to address and the evidence needed to move forward.

  3. Build

    Design and engineer coherent slices with regular product validation.

  4. Deliver and iterate

    Deploy, document, maintain and then evolve what real usage makes important.

Questions to answer before writing code.

The first conversation checks fit as much as it helps estimate the work.

Does the need have to be fully scoped already?

No. A goal, its users and a few constraints are enough to start. Framing is part of the engagement.

Can one person cover the entire product?

I take responsibility for a substantial scope end to end and make clear when complementary expertise becomes useful.

How do we keep an AI feature from remaining a prototype?

By designing the use case, data, controls, cost and product integration together from the start.

Can we begin with a short engagement?

Yes. An audit, prototype or focused sprint can produce the decision needed before a larger commitment.