Layer 2 · reasoning
AI + Quantum Trust Brain
AI detects. Quantum-inspired search optimises over admissible options. The policy gate verifies. Nothing here can relax a hard constraint — the constraint is the search boundary, not a preference.
Model bank
Nine model families over one signal field
Identity AI
97.2Transformer entity resolution across channels
Fraud AI
94.8Gradient ensemble on payment + device features
Graph AI
93.3GNN over beneficiary and mule topology
Behaviour AI
91.7Sequence model on session and velocity
Deepfake AI
96.1Frame + audio synthesis artefact ensemble
Agent AI
90.5Scope adherence and prompt-injection defence
Signal-Wave AI
88.9Phase-sequence detection across signal fields
RAG / SLM
94.0Policy retrieval over RBI, DPDP and bank circulars
Digital Twins
92.6State reconstruction and counterfactual replay
Live signal field
Composite input to the brain
Inference rate
14.2k/s
Model drift
0.7%
30-day
Quantum / Q-inspired optimizer
min (Cost + Latency + λ·PrivacyExposure) s.t. IdentityConfidence ≥ threshold
Achieved confidence
95.3%
Objective cost
49.0
Convergence (annealing schedule)
Minimum necessary evidence set
2 evidence sources withheld — data the platform is entitled to request but does not need to satisfy the confidence floor.
Solution certificate
Reproducible, auditable, signed
{
"problem": "minimum_necessary_evidence",
"form": "QUBO / binary constrained",
"constraint": {
"identity_confidence_min": 0.95
},
"lambda_privacy": 1,
"solution": [
"aadhaar_offline_xml",
"device_attest",
"face_liveness",
"sim_binding",
"ckyc_record"
],
"achieved_confidence": 0.9534,
"objective": 49,
"verified_by": "exhaustive_classical_check",
"overrides_policy": false
}Quantum explainability
Objective, constraints and why the search wins
The deterministic layers above run without AI. Generate a narrative to add a plain-language explanation of the current state for reviewers and supervisors.