An AI model can answer. An organization also needs to know what task was set, what information was used and who is responsible for the outcome.
The starting point
AI is often introduced as a single tool: an interface, a model, a quick prompt. In real work, people, data, knowledge, applications and decisions meet. Value emerges when those parts fit together.
AGInC develops coordination architectures for this collaboration. They are intended to organize tasks and responsibilities, keep sources and assumptions visible, and show where automated support passes into human decision-making.
The question is not only what a model can do. It is how its result enters an accountable workflow.
LILISA: collaboration as architecture
LILISA is the AGInC architecture for collaboration among specialized AI instances and people. Different tasks may call for different models, tools and sources of knowledge. The architecture is intended to coordinate these contributions while preserving their origins and limits.
A possible workflow starts with a defined task and context. It separates research from assessment, drafting from review, and a proposal from a decision. Changes to models or tools should not silently shift responsibility.
This describes a development direction. It does not claim that every capability shown is already available as a finished service.
Knowledge needs provenance
Convincing text can rest on uncertain foundations. AGInC therefore keeps source, observation, assessment, open question and decision distinct. An existing document is not automatically a valid answer in a later context.
When facts, providers, deadlines or requirements change, earlier versions remain identifiable as earlier versions. Relevant consequences require fresh review.
People remain responsible
Automated systems can find connections, prepare options and point out missing information. They should make clear what they know, what they assume and where they must abstain.
Consequential approvals, legal assessments, external communication and production changes require decisions by the responsible people. AGInC treats this boundary as part of the architecture.
AGIREG: regulatory questions in project context
AGIREG grew out of the AGInC/LILISA work. The internal AGInC Regulatory Intelligence & Evidence Graph connects regulatory research with project facts, evidence, changes and open decisions. It is a protected layer within the architecture; a separate service for organizations and projects is in development.
AGIREG is intended to make relevant questions and responsibilities visible. It does not replace case-specific legal or expert review or automatically declare a project compliant. See the AGIREG website for details.
Development with clear limits
AGInC combines research, system design and practical exploration. The maturity of each capability and use case differs. This website explains the direction and selected work in progress; it is not a general promise of availability or performance.
To discuss a specific context, contact the AGInC project at info@aginc.ai.