The challenge
Researchers increasingly use AI tools, but prompts, evidence, decisions, corrections and outputs are often disconnected. This makes quality, provenance, supervision and reuse difficult.
Emerging research initiative
KCS RESEARCH PROJECT
KAIRO
An emerging initiative for structured, AI-supported research work
KAIRO explores how research knowledge, AI assistance and explicit workflows can help researchers move from an open question to traceable evidence, reviewed outputs and reusable knowledge. Its public specification is being consolidated as the initiative develops.
Explore the project architectureResearch questions
The questions connect the real-world problem with research activities and evaluable contributions.
- How can AI assistance remain connected to evidence and researcher decisions?
- Which workflow supports transparent review, correction and supervision?
- How should research artefacts, prompts, sources and outputs be organised for reuse?
- Where must human judgement remain authoritative?
The research-project architecture
The KAIRO architecture connects the project context and research assets with the methods, systems and outcomes required to answer its research questions.
CONTEXT
Researchers and supervisors
Students and early-career researchers
Experienced researchers
Supervisors and research leads
→ASSETS
Research knowledge
Questions and plans
Sources, data and notes
Reviews, decisions and corrections
→METHODS
Responsible assistance
Explicit research workflow
Human verification
Traceability and quality gates
→SYSTEM
KAIRO concept
Structured research workspace
AI-supported activities
Reusable templates and records
→OUTCOMES
Research capability
Clearer decisions
Reviewed written outputs
Transferable research knowledge
Project architecture: KAIRO connects real needs and research assets with controlled methods, reusable systems and transferable outcomes. Evaluation and feedback can return the project to an earlier facet.
Research workstreams
Each workstream addresses a distinct part of the project while remaining connected to the shared architecture and questions.
Research workflow
Connect direction, planning, literature, design, implementation, evaluation and writing.
AI-assisted activities
Define where AI can help and what evidence, review and correction are required.
Supervision and quality
Make questions, feedback, decisions and accepted outputs visible.
Knowledge reuse
Organise reusable methods, examples and project records without exposing confidential material.
Project highlights
- The KCS research lifecycle, starter packs and supervision procedures provide the methodological foundation.
- Current work focuses on defining the public concept, target users and demonstrable pilot.
Research and supervision
KCS supports students, researchers and supervisors in connecting a relevant problem with appropriate methods, careful evaluation and a clear written or technical result.
Ways to participate or collaborate
- Researchers may contribute real workflow needs and pilot scenarios.
- Supervisors and institutions may discuss responsible AI-assisted research training.
- Partners may explore a comparable research-support workflow or software concept.
ENGAGE WITH KCS
Could this research direction help you or your institution?
Tell KCS whether you want to learn the method, join or propose a project, supervise researchers, evaluate a related idea, or develop a comparable research and innovation programme.
CONTACT / APPOINTMENTS
Contact / Termine
If you are interested in further information, or have comments or suggestions, please send them using the contact options below.
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