Keep research knowledge
independent.
Keep research rules and records separate; validate compatibility when changing models.
Models change.
Research knowledge endures.
Separate domain knowledge from the model interface. Review deployment and permissions before implementation.
Lean orchestration.
Deep domain skills.
Integration & controlled write-back
Standard APIs · audit logs · human approval
Through agreed interfaces;
no direct database reads or writes.
Domain skills & memory
Research rules · analytical methods · working context
Knowledge stays with the client
when the model changes.
Harness runtime · thin layer
Execution primitives only;
domain logic lives in skills.
Foundation models
Proprietary · open-weight · locally deployed
Replaceable;
validate before switching.
Client-owned assetsReplaceable infrastructure
Conceptual architecture. Model changes still require compatibility checks and task validation.
Keep research knowledge
Make permissions explicit.
Agree read/write permissions and human review before implementation.
Deployment follows
the agreed boundary.
Agree deployment, data flows and support access with technology and compliance teams.
Your data.
Your research knowledge.
Your institutional data and research knowledge remain yours. We design the workflow around your access requirements and agreed operating environment.
An agreed data boundary
Agree deployment, model-service access and data flows before implementation. Processing and support access follow the approved scope.
Controlled access and records
Define access roles, human review and execution records with your technology and compliance teams.
Knowledge that stays with you
The knowledge base belongs to your institution and supports full export. Research rules, sources and records remain independent of model interfaces, with handover arrangements agreed in writing.
Discuss your research needs.
Define the next step.
A complimentary 30-minute consultation to discuss your research needs and explore the next step.
Book a free consultation