End-to-end deterministic AI. Not another model.
The full path from encoding to delivery — for financial services and insurance teams who must defend every decision.
Deterministic AI stack
- L5 RuntimeEnterprise
Neural Symbolic Agents
Orchestrates multi-agent workflows. Defends decisions end-to-end.
- L4 MemoryRequest demo
Quantum Graph Memory
Time-aware graph memory (QGM). Preserves provenance across sessions.
- L3 GenerationRequest demo
Qualtron
Composite 4M-context specialized models for regulated output.
- L2 ReasoningPublic preview
QAG Engine
Seven HSC signals: Relevance, Conflict, Overlap, Redundancy, Coverage, Coherence, Topology.
- L1 FoundationLive
Q-Prime
Quantum-structured embedding model. Encodes polarity, scope, conditions, dependencies.
+ Delivery — Enterprise Blueprints ship every layer into production workflows.
Traditional RAG gives you a confidence score. Chunkless RAG gives you a defensible decision.
Regulators ask which rule and which conflict produced the outcome — not a confidence score.
Traditional RAG
Chunk, retrieve, compose. Probabilistic.
- Chunks lose structure and cross-rule dependencies
- Different rationales from the same prompt
- No trace a regulator can replay
Chunkless RAG (QAG)
Encode, reason, defend. Deterministic.
- Q-Prime encodes the full corpus — polarity, scope, dependencies
- QAG Engine surfaces contradictions as seven decision signals
- Every decision traceable and replayable
Encode → reason → orchestrate → deliver.
Each layer is independently auditable. Start with Q-Prime, add Chunkless RAG, graduate into Custom Agents.
Q-Prime
Quantum embeddings
The first commercial quantum-structured embedding model. Encodes enterprise data into a hypergraph that preserves polarity, scope, and cross-rule dependencies. Runs on NVIDIA CUDA-Q — no QPU required.
QAG Engine
Chunkless RAG for regulated decisions
QAG reasons over whole documents instead of chunked retrieval. A Hilbert-Space Compacting layer projects document states into seven interpretable signals before generation, so contradictions surface as explicit audit signals.
Qualtron
4M-context composite model
Specialized small models that compose into a 4M-token working context for regulated generation. Replaces general-purpose LLMs inside QAG where domain precision beats raw scale.
Quantum Graph Memory
Time-aware graph memory
Graph memory for QAG agents. Preserves provenance and temporal structure of every fact and revision, so reasoning stays consistent across sessions and audits.
Neural Symbolic Agents
Custom agents for FS workflows
The runtime layer of the stack. Orchestrates underwriting, claims, fraud, and compliance with persistent memory, dependency tracking, and conflict coordination that survives audit replay.
Live artifacts, enterprise evaluations, published record
Enterprise evaluations
Evaluations in progress
Regulated teams evaluating QGI inside AI Governance frameworks.
Live artifact
Q-Prime on HuggingFace
Model card and managed-API access to the foundation layer.
Published record
20 peer-reviewed papers
Formal verification and decision-structure research behind the architecture.
Questions teams ask before a demo
What is Chunkless RAG?
QGI's QAG approach: encode the full corpus via Q-Prime, reason over structure with the QAG Engine, and deliver via Enterprise Blueprints — not chunk-and-retrieve.
How does the platform fit together?
Q-Prime encodes. QAG Engine reasons. Custom Agents orchestrate. Blueprints deliver. Qualtron and QGM extend the stack on the 2026 roadmap.
Do I need quantum hardware?
No. Q-Prime and the QAG Engine run on NVIDIA CUDA-Q and cuTensorNet on commodity GPUs.
Is Q-Prime open source?
Available on HuggingFace as a managed API under the QGI Commercial Model License v1.0. Weights are not distributed. SDKs are on GitHub.
Can QGI deploy on-premise?
Yes. Enterprise engagements include VPC and on-premise options. See the Trust page for deployment models.
Ready to deploy decision-grade AI?
We run a small number of demos per quarter in financial services and insurance.