Privacy rules and poor accuracy capped AI use at 30%. A self-hosted model hit 90% precision, driving adoption to 100%.
A global system integrator with 350,000 employees across 40+ countries serves clients in highly regulated sectors like aerospace, defense, and the public sector.
Strict data sovereignty rules prevented the use of cloud-based AI, while initial open-source attempts stalled at 30% adoption due to poor accuracy....
“Leveraging Mistral’s Codestral has been a game changer in the adoption of private software engineering assistants for our client projects in regulated sectors. We have evolved from providing basic support for some development activities to delivering systematic value for our development teams.”
Capgemini's Code generation is part of this use case:
IT consulting and digital transformation services for global enterprises.
Mistral AI is a company that specializes in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Developers hand-coded complex business logic from scratch. Now, 2,000 engineers use AI to generate it directly from detailed design docs.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Developers hand-coded complex business logic from scratch. Now, 2,000 engineers use AI to generate it directly from detailed design docs.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Lawyers manually reviewed 300-page technical reports. AI now scans the docs to draft affidavits and witness tables instantly.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Privacy rules and poor accuracy capped AI use at 30%. A self-hosted model hit 90% precision, driving adoption to 100%.
A global system integrator with 350,000 employees across 40+ countries serves clients in highly regulated sectors like aerospace, defense, and the public sector.
Strict data sovereignty rules prevented the use of cloud-based AI, while initial open-source attempts stalled at 30% adoption due to poor accuracy....
“Leveraging Mistral’s Codestral has been a game changer in the adoption of private software engineering assistants for our client projects in regulated sectors. We have evolved from providing basic support for some development activities to delivering systematic value for our development teams.”
Capgemini's Code generation is part of this use case:
IT consulting and digital transformation services for global enterprises.
Mistral AI is a company that specializes in artificial intelligence and machine learning solutions.
Related implementations across industries and use cases
Developers hand-coded complex business logic from scratch. Now, 2,000 engineers use AI to generate it directly from detailed design docs.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Developers hand-coded complex business logic from scratch. Now, 2,000 engineers use AI to generate it directly from detailed design docs.
Technical debt in large codebases hindered velocity. Now, AI handles execution-heavy updates while engineers retain merge approval.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Lawyers manually reviewed 300-page technical reports. AI now scans the docs to draft affidavits and witness tables instantly.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.