Enterprise Blueprints
E2E deterministic AI delivery
Four lanes for regulated teams: workflow repos, private runtime, operating model, custom agents — wired to Q-Prime and Chunkless RAG (QAG).
Four delivery lanes
- 1 Workflow blueprints Reference repos for regulated retrieval. Documents QAG upgrades Traditional RAG to Chunkless RAG for FS and insurance policy corpora.
- 2 Private AI runtime Data stays in your boundary. Route by risk class — escalate to Chunkless RAG when output must survive audit.
- 3 Production AI operating model Versioned prompts, review gates, demo-to-production discipline. Enterprise Factory patterns, not disconnected demos.
- 4 Custom agent blueprints Mortgage reviewer, claims triage, AML investigator — wired to Q-Prime and the QAG Engine.
Integration catalog — Traditional RAG to Chunkless RAG
Integration catalog wired to Q-Prime and QAG. Documents QAG is the anchor — Traditional RAG → Chunkless RAG for policy corpora.
Documents QAG
NVIDIA's reference retrieval blueprint, forked into the Enterprise Factory and reshipped as Documents QAG — wired to Q-Prime so contradictions in policy, contract, and regulatory corpora surface as structured signals before generation. Classical RAG becomes deterministic QAG.
Video Search & Summarization
Ingest massive volumes of live or archived video and extract insights for summarization and interactive Q&A. QGI pass adds QAG reasoning for cross-clip contradiction detection and timeline-consistent recall.
AI-Q Reasoning Agents
Reference implementation for intelligent agents that connect to enterprise data, reason with SOTA models, and deliver trusted insights. QGI swaps classical embeddings for Q-Prime so every step is deterministic and auditable.
Retail Agentic Commerce
Reference implementation of the Agentic Commerce Protocol (ACP) and Universal Commerce Protocol (UCP) — AI-powered checkout negotiation with merchant control preserved. Q-Prime validates policy compliance at each step.
Retail Catalog Enrichment
GenAI-powered catalog enrichment that transforms basic product images into comprehensive catalog entries. Q-Prime enforces attribute consistency and flags category-level conflicts at scale.
Multi-Agent Intelligent Warehouse
Multi-agent logistics and warehouse coordination. QAG's conflict signals resolve scheduling contradictions across agents before they execute, turning agent swarms into auditable decision chains.
Content Localization
Localize and translate media with lip-synced dubbing across multiple speakers. QGI layer enforces regulatory-text equivalence so translated compliance and legal copy preserves meaning, not just words.
BioNeMo Framework
Foundation for building and adapting AI models for drug discovery at scale. QGI adds quantum-structured representation for molecule-property reasoning and clinical-rule compliance across pipelines.
Climate AI Workflows
Open-source deep-learning framework for exploring, building, and deploying AI weather and climate workflows. Q-Prime adds regulation-aware scenario reasoning for ESG disclosure and catastrophe insurance.
QGI Inference Engine
A high-performance serving framework for LLMs and multimodal models — QGI's fork of SGLang, tuned for Q-Prime workloads and CUDA-Q co-execution on commodity GPUs.
QGI cudaqx
Accelerated libraries for quantum-classical computing built on CUDA-Q — the substrate QAG runs on for interactive latency on compliance-scale corpora without requiring quantum hardware.
Google Flights MCP
Travel-search MCP server and Python library. Wired into QGI agents as a tool layer so Q-Prime can reason about policy constraints (duty of care, class-of-service, carbon budget) at booking time.
Documents QAG — classical RAG, remade deterministic
NVIDIA RAG fork with Q-Prime encoding and QAG reasoning — deterministic retrieval for mortgage overlays and policy intake.
See Documents QAG →Traditional RAG
Vector similarity → generator
Similarity scores hide polarity and contradictions.
Chunkless RAG (QAG)
Q-Prime → HSC signals → QAG Engine
Conflicts surface as explicit signals before generation.
Data in your boundary. Routing by risk class.
Route by risk class. Escalate to Chunkless RAG when a probabilistic answer won't survive audit.
Design private AI routing →Escalation path
Private models for extraction; Q-Prime + QAG for signable decisions.
Data boundary
Classify sensitive data before routing. Private by default — VPC or on-prem.
Tiered model routing
Local models for drafting; Chunkless RAG when the answer must be replayable.
Audit escalation
Fast extraction on private models; escalate to Q-Prime + QAG on policy conflicts.
Evidence capture
Prompts, tool calls, decision traces — reproducible under examination.
From demo to production — one operating rhythm
Versioned policies, review gates, demo-to-production — one rhythm your board and auditors can follow.
Versioned prompts and policies
Prompts and policy overlays as versioned assets — not scattered chat history.
Review gates
Human review and governance checkpoints before production promotion.
Demo to production
Start with one regulated workflow, expand without restarting from notebooks.
Enterprise Factory patterns
Reusable repos and audit surfaces shared by engineering and compliance.
How it connects
Factory repos + runtime policy + agent blueprints = production delivery.
Regulated agent workflows for financial services and insurance
Pre-scoped agents for workflows where a wrong answer is an audit event.
Mortgage reviewer
ActiveOverlays and guidelines — surface conflicts, coverage gaps, deterministic narratives.
Claims triage
PreviewFNOL intake through policy retrieval. Escalate ambiguous cases to Chunkless RAG.
AML investigator
EnterpriseAlerts, KYC evidence, rule corpora — replayable investigation graph.
Questions teams ask about end-to-end Blueprint delivery.
What are QGI Enterprise Blueprints?
How is Chunkless RAG different from Traditional RAG?
Runtime and repos, or just reference code?
Can I deploy in my own environment?
How does licensing work?
Don't see your vertical?
Bring your base — we'll mix it with Q-Prime and Chunkless RAG for your regulated workflow.