arKItect SEA
Systems Engineering Advanced (SEA) is a single engineering database to synchronize, verify the consistency and completeness of all system engineering data. It offers an easy-to-use collaborative environment for the modelling of complex systems and for the definition of systems specifications.
arKItect Designer
Designer is our data integration platform enabling structuring, visualizing, and operating complex set of data stemming from various legacy sources (Excel™, database, web sites, xml…) or edited directly through arKItect collaborative interface Flyer (Designer Flyer)
arKItect-MCP
arKItect-MCP gives AI controlled access to project data, model operations, and reusable engineering skills, while arKItect validates every change against the data model, business logic, and formal consistency rules. AI becomes operational, but arKItect remains the authority.
GRAISS
GRAISS lets users query a document corpus in natural language and receive structured, verifiable answers with precise sources.
Unlike a standard RAG system, it answers only from your documents and explicitly states when information is missing.
Designed for professional use, it secures document analysis for tenders, regulations, technical documentation, claims, risks, and compliance
Formal harness
The integrated AI-assisted engineering environment that combines arKItect components with generative AI, model-specific skills, scripts, APIs and verification mechanisms.
It combines:
- arKItect, as the structured engineering repository and model-based platform;
- arKItect MCP, as the controlled interface through which LLMs can query, navigate, modify, and use the engineering model;
- formalized data models, model-specific skills, viewpoints, rules, APIs, and formal verification mechanisms;
- model scripts and programs, including agents operating inside the model when relevant;
- generative AI models, used as interchangeable reasoning and generation engines.
Together, these components allow AI to work inside a traceable engineering process rather than outside it. The model provides context, constraints, memory, structure, and control; the LLM provides language understanding, generation, and assistance.
The Formal Harness is also designed to be deployed on a sovereign AI stack when required.
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