Claim/evidence graph
Public documents can be converted into structured claims, source references, evidence weights, provenance notes, and review tasks for a human-led audit process.
Controlled-access research PoC lane
Quantum-Ready Evidence and Provenance Workflow
QuantumEncryption1 can support a research-ready workflow for provenance-aware evidence graphs, AI claim extraction, audit ledgers, and quantum or simulator optimisation tests. The initial scope uses non-sensitive public or synthetic data only.
Strategic fit
Why this belongs beside QuantumEncryption1
The core QE1 site already focuses on protected files, provenance, audit language, IonQ-ready evidence, and controlled access. This lane extends that public position into a measurable research workflow rather than a broad production claim.
Auditable handling trail
Each run can produce a controlled report containing document fingerprints, extraction settings, reviewer notes, model limitations, baseline scores, and comparison records.
Candidate optimisation tests
Quantum-cloud or simulator methods can be evaluated as candidate ranking, routing, search, or comparison experiments alongside classical baselines.
PoC boundary
Initial PoC uses non-sensitive public/synthetic data only
The first phase should not require confidential uploads, controlled documents, patient records, classified material, export-controlled files, private keys, or production security data.
Safe starting data
What can be used first
Public policy papers, open research abstracts, public procurement notices, synthetic incident reports, sample energy or transport records, and generated test corpora are suitable for early evaluation.
The aim is to validate architecture, evidence quality, measurement method, and reviewer workflow before any sensitive deployment discussion.
Technical architecture
Measured evidence pipeline
The architecture is deliberately reviewable. Classical baselines stay in the evaluation loop so quantum or simulator methods are measured rather than assumed to be superior.
QE1 / evidence workflow
Public documents -> AI extraction
AI extraction -> claim/evidence/provenance graph
claim/evidence/provenance graph -> classical baseline
classical baseline -> quantum/simulator candidate methods
candidate methods -> comparison
comparison -> auditable report
Student and researcher route
Using ZeroThink Paper Creator for survey expansion
This workflow is available inside the ZeroThink Research Paper Creator and Nottingham research lanes. It is not the default ZeroThink chat mode, because the evidence graph, source ledger, and optimisation plan need a staged academic workflow.
Start with seed papers
Collect two to five articles, abstracts, DOI links, BibTeX records, or paper notes. Upload or paste them into Paper Creator and choose the survey expansion evidence graph option.
Build the evidence graph
Run Search Protocol, Evidence Plan, Evidence Graph, and Source Ledger before drafting. Each claim should map to a source or be marked as a candidate lead.
Test optimisation ideas
Run the Optimisation Test as a PoC plan for evidence-path selection, clustering, routing, prioritisation, and auditability scoring, then compare against a classical baseline.
Fundable options
Research and innovation scopes
Each option starts with a written scope, safe dataset plan, evaluation method, deliverables, and access boundary. This is a research-ready PoC lane, not a production-certified government system.
3-month PoC
Build a public/synthetic dataset, extraction schema, evidence graph, classical baseline, simple audit ledger, and final review report.
6-month PoC+
Add multiple sectors, reviewer scoring, reproducibility packs, richer provenance records, simulator experiments, and a partner-facing demonstration.
Defence/security scoping
Map the evidence workflow against security review needs using non-sensitive examples, clear disclaimers, and controlled access boundaries.
Healthcare/transport/energy mapping
Create sector-specific synthetic scenarios and show how claims, evidence, risk notes, and provenance records can be reviewed without exposing live records.
Quantum-cloud telemetry/context layer
Record provider job context, simulator settings, timestamps, fingerprints, and comparison notes as part of an auditable evidence package.
Assurance boundary
What this is not
The page is intentionally careful about public-sector, quantum, and AI claims. It sets a useful PoC direction without implying approval, certification, or confidential access.
Not claiming quantum computers understand documents
Document understanding remains an AI and human-review task. Quantum or simulator tests are candidate optimisation experiments, not semantic comprehension.
Not claiming MOD, UKRI, NQCC, DSIT, IBM, or IonQ approval
Any named organisations are referenced only as relevant ecosystem context or technology providers where applicable. No sponsorship, approval, certification, or endorsement is claimed.
Not requiring confidential uploads
The initial PoC is designed to use public or synthetic data. Do not submit classified material, production security data, passwords, keys, or confidential records through the public website.
Controlled enquiry
For approved organisations, funders, universities, and public-sector innovation teams.
Use the contact route to request a scoped discussion. Include your organisation type, sector, intended public/synthetic data source, preferred PoC length, and any review constraints.