Observe
Scientific literature · rendered web
Existing product inputsTECHNOLOGY / RESEARCH VISION
Make intelligence accountable to evidence.
A proposed architecture for observable, verifiable and reliable AI systems. Existing product capabilities are the foundation; a unified VERIFY platform remains a research objective.
THE PROPOSED STACK
From observation to review.
Reason
Source-linked analysis · structured outputs
Product-specific capabilitiesVerify
Evidence graph · quality checks · provenance
Proposed shared R&DReview & act
Human escalation · auditable decisions
Proposed integration layerConceptual design. This diagram does not represent a deployed shared service or a guarantee of correctness.
RESEARCH QUESTIONS
Defensibility must be demonstrated.
Evidence graphs
Can claims, sources and contradictions be represented in a way that makes a conclusion reproducible?
Evaluation protocols
Can domain-specific benchmarks detect failures that a generic model score misses?
Multimodal verification
Can rendered web observations validate an agent’s intended action against the actual result?
Human oversight
Which uncertainty signals should trigger review, and how should expert feedback improve the system?
2027–2028 / R&D
Progress through evidence gates.
An indicative research sequence, contingent on funding, expertise and pilot validation. No availability date is committed.
- 01
Foundation
Map reusable technology and IP. Establish evaluation baselines and validate buyer needs.
- 02
Research prototypes
Prototype evidence graphs and visual action checks with prospective design partners.
- 03
Pilot validation
Test a shared API in bounded workflows. Compare results against expert review and failure cases.
- 04
Industrialisation
Advance reliability, security and repeatable enterprise delivery when pilot evidence supports it.
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