ASM2 AUTO
Contact details:
Company: In2AI INTELLIGENCE S.L.
Contact: Manuel Ruiz
Telephone: +34 616 466 446
Email: manuel@in2ai.com
Web: www.in2ai.com
LinkedIn: www.linkedin.com/company/in2aiÂ
Project description:
ASM2 Auto is the adaptation of In2AI’s conversational assistant to the automotive and mobility sector. The platform is designed to improve operational efficiency, knowledge management, and decision-making in organizations where information is dispersed across PLM, ERP, MES, QMS, SharePoint, local folders, manuals, procedures, and document repositories. Its goal is to turn heterogeneous documentation and unstructured corporate knowledge into useful, traceable, and secure answers for quality, operations, maintenance, engineering, procurement, or internal support teams.
Solution & technologies:
The solution combines natural language processing, generative AI, RAG, LLMs, semantic search, connectors to document repositories, automatic indexing, role-based access control, sensitive information filtering, traceability, and monitoring. ASM2 Auto supports on-premise or hybrid deployment, with software installed where the client’s information resides and a private web service for configuration, administration, and monitoring. This approach ensures that data does not leave the organization, facilitating compliance with confidentiality and privacy requirements in sensitive industrial environments.
Innovation contributed:
ASM2 Auto innovates by transforming dispersed corporate knowledge into specialized assistants capable of responding with context, evidence, and permission control. Its key differentiator is that it does not require migrating repositories or modifying existing operational workflows: it connects to knowledge where it already resides, reusing what is generated in incidents, improvements, and internal documentation. It can be deployed in a single unit or across multiple entities simultaneously, where each one accesses exclusively the information it is entitled to. Governance over who can access what is not a secondary feature, but the core of the model, making it viable even in highly compartmentalized structures or environments with strict confidentiality requirements.