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Ministry of the Interior: accelerating the transformation of the State through AI with concrete products for agents

Structuring the MiRAI product organization and putting into production of FCR, a tool for automatically generating reports.

background

As part of the LOPMI (Law on Orientation and Programming of the Ministry of the Interior) and the interministerial roadmap on AI, the Ministry of the Interior has launched miRAI, a structuring program to industrialize AI tools useful to agents.

The challenge is twofold: to accelerate the production of concrete AI products aimed at saving time for agents (transcription, writing, automation, etc.); to structure a sustainable product organization, capable of identifying good use cases, of delivering quickly, and of industrializing solutions.

To begin this dynamic, the SDID (Sub-Department of Innovation and Data of the Ministry of the Interior) entrusted Theodo with a double mission: to structure the miRAI organization (vision, discovery, delivery); to deliver a first AI product: FCR, a tool for helping to write reports.

This project laid the foundations for an AI product factory within the state.

Challenges

  • Refocus a portfolio of initiatives around a clear product strategy (MiRAI Chatbot, OCR, FCR, Text Summary...);
  • Accelerate delivery on complex technical bases (CloudPi Native, n8n base, sovereign AI), while increasing tech quality (tests, CI/CD, code coverage,...);
  • Structure a functional product organization with an industrializable discovery approach to capture the real needs of agents and prioritize projects;
  • Hold ambitious political and business milestones, such as demonstrations for ministerial sponsors.

Our approach

7 Theodo experts (1 Lead PM, 1 Product Owner, 1 UX/UI Designer, 1 Tech Lead and 3 Software Engineers) accompanied the SDID.

What made the difference:

Just-in-Time

Implementation of a retroplanning 4 weeks before the arrival of the devs to align all actors and avoid waste.

Right-First-Time

Standardization of the code (tests, CI/CD, linters) to industrialize delivery from Sprint 0.

Our impact

4 months

to deliver FCR, with configuration of a speech-to-text transcription brick, identification of speakers, editing of reports.

+30%

intended to be used in a real situation after testing.

Product base

industrializable, already extended to other AI use cases.

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