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Quantum Pipes Documentation

Intelligence that belongs to you.

Quantum Pipes is an offline-first AI platform with cryptographic accountability. Infinite capabilities. Complete sovereignty. Runs on your hardware, proves what it did, and your data never leaves.

100% Local. Zero Cloud. Air-Gap Ready.

License Python Go


Why Quantum Pipes?

Most AI platforms ask you to trust them with your data. Quantum Pipes makes trust unnecessary by making everything provable.

Infinite capabilities, not one chatbot. Research, legal analysis, code generation, security audit, compliance checks, voice transcription, and anything else you need. When a capability doesn't exist, the system creates it. Every other platform has a fixed capability list. Quantum Pipes doesn't.

Honest AI. Admits uncertainty. Confidence scores on every claim. Reasoning recorded before execution, not after.

Complete sovereignty. Zero egress firewall. Models run locally. Data physically cannot leave your infrastructure. Not by promise, by architecture.

Cryptographic proof. Post-quantum signatures on every decision. Hash-chained audit trail. 48 conformance test vectors. Verifiable from Python, TypeScript, or Go.


Open Source Packages

Quantum Pipes is a composable ecosystem of independent packages. Use one, use all.

Audit and Accountability

Package Purpose Install
qp-capsule Audit protocol: CPS v1.0 spec, 6-section records, hash-chained, dual-signed pip install qp-capsule
capsule-go Go verification: Capsule integrity, chain linkage, Ed25519 signatures (stdlib only) go get github.com/quantumpipes/capsule-go
capsule-litellm LLM bridge: one-line audit trail for any LLM call via LiteLLM pip install capsule-litellm

Knowledge and Orchestration

Package Purpose Install
qp-vault Knowledge store: 4 trust tiers, hybrid search (70% vector + 30% keyword), Merkle verification pip install qp-vault
qp-conductor Orchestration: goal decomposition, 5 autonomy levels, agent swarms, adaptation engine pip install qp-conductor

Infrastructure

Package Purpose Install
conduit Internal infrastructure: auto-DNS, auto-TLS, service routing, GPU monitoring Shell scripts
tunnel Secure boundary: WireGuard + post-quantum TLS, 57 concurrent services, 9 CLI commands Shell scripts

How It Works

┌─────────────────────────────────────────────────────────┐
│  You describe a goal in plain language                   │
└────────────────────────┬────────────────────────────────┘
                         v
┌─────────────────────────────────────────────────────────┐
│  CONDUCTOR matches your goal against known capabilities   │
│  Synthesizes novel ones when nothing fits                │
│  Assigns autonomy level (L0-L4), dispatches agents       │
└────────────────────────┬────────────────────────────────┘
                         v
┌─────────────────────────────────────────────────────────┐
│  Agents execute: PERCEIVE > REASON > DECIDE > ACT        │
│  Each agent has tools, knowledge (Vault), and policies   │
│  Every iteration checks the kill switch                  │
└────────────────────────┬────────────────────────────────┘
                         v
┌─────────────────────────────────────────────────────────┐
│  Every action seals a CAPSULE                            │
│  Trigger > Context > Reasoning > Authority > Execution   │
│  > Outcome. SHA3-256 hashed. Ed25519 + ML-DSA-65 signed │
│  Hash-chained into immutable temporal ordering           │
└─────────────────────────────────────────────────────────┘

Package Deep Dives

Capsule: The Audit Protocol

The irreducible foundation. Every AI action in the ecosystem seals a Capsule.

forall action: exists capsule

A Capsule is a tamper-evident record with six sections:

Section What It Captures
Trigger What initiated this operation (type, source, timestamp, request, correlation ID)
Context Environment at decision time (agent ID, session, environment)
Reasoning Pre-execution analysis (options considered, selected option, confidence, model, prompt hash)
Authority Who approved and under what policy (approver, policy reference, escalation reason)
Execution What actions were taken (tool calls, duration, resources used)
Outcome Results and side effects (status, result, summary, error, metrics)

Cryptographic sealing:

  • SHA3-256 content hash (Keccak sponge construction)
  • Ed25519 digital signature (classical)
  • ML-DSA-65 post-quantum signature (FIPS 204)
  • Hash chain linking each Capsule to its predecessor

8 Capsule types: agent, tool, system, kill, workflow, chat, vault, auth

3 language SDKs:

Language Package Capabilities
Python qp-capsule Create, seal, verify, SQLite/PostgreSQL storage, CLI, FastAPI integration, @capsules.audit decorator
TypeScript @quantumpipes/capsule Create, seal, verify, chain validation, canonical JSON
Go capsule-go Verify hash, verify signature, chain checks, canonicalize

48 conformance test vectors ensure cross-language interoperability.

Content-addressable URI scheme:

Form Example Use case
Hash capsule://sha3_7f2a4b8c... Content-addressable lookup
Chain + Sequence capsule://chain/42 Chain-relative reference
UUID capsule://550e8400-... Direct record lookup
Fragment capsule://sha3_...#reasoning/confidence JSON Pointer into sections

Vault: Governed Knowledge

Content-addressed storage with trust tiers that affect search ranking.

4 trust tiers:

Tier Search Boost Purpose
CANONICAL 1.5x Source of truth. Verified, immutable reference documents.
WORKING 1.0x Active documents under development or revision.
EPHEMERAL 0.7x Temporary context. Automatically cleaned up.
ARCHIVED 0.25x Historical records. Searchable but deprioritized.

Hybrid search: 70% pgvector semantic similarity + 30% pg_trgm keyword matching, multiplied by trust tier boost and freshness score.

4 data classifications: PUBLIC, INTERNAL, CONFIDENTIAL, RESTRICTED

6 lifecycle states: DRAFT, REVIEW, ACTIVE, SUPERSEDED, EXPIRED, ARCHIVED

3 memory layers: OPERATIONAL (fast, recent), STRATEGIC (organizational knowledge), COMPLIANCE (regulatory, immutable)

Integrity verification: Merkle tree verification, contradiction detection, staleness detection, duplicate identification. Content-addressed with SHA3-256.

Conductor: Cognitive Orchestration

Decomposes natural language goals into capability-ordered execution plans. Ships with a broad set of seed capabilities. When a goal requires something that doesn't exist yet, the Capability Synthesizer creates it. The capability surface is infinite.

How it works:

You describe a goal. Conductor analyzes it against known capabilities. When nothing matches, the Capability Synthesizer composes a novel capability from a cognitive substrate of operators. The synthesized capability is registered, executed, scored with Joy, and improved through feedback. Over time, the system grows more capable without manual authoring.

New seed capabilities can also be added by dropping a YAML file in the registry directory.

5 autonomy levels:

Level Name Oversight When to use
L0 BLOCKED Full stop. Human must initiate. Destructive operations on production systems
L1 SUPERVISED Every step reviewed. Sensitive financial or legal tasks
L2 CHECKPOINT_MAJOR High-risk steps reviewed. Mixed-risk workflows
L3 CHECKPOINT_END Final output reviewed. Default. Most tasks.
L4 FULL Audit trail only. Low-risk, high-confidence, established track record

Broad seed coverage: Ships with capabilities spanning analysis, audio, communication, creation, cybersecurity, data, education, engineering, governance, investigation, linguistics, mathematics, medicine, operations, planning, science, strategy, sysadmin, validation, and more.

+ Infinite synthesis. When no existing capability matches a goal, the Capability Synthesizer creates one from a cognitive substrate of operators. Synthesized capabilities are cached, executed, scored, and improved through feedback. The system gets better at tasks it has never seen before.

8 subsystems:

Subsystem Function
Goal Analyzer Natural language to capability requirements with intent classification
Capability Composer Requirements to dependency-ordered execution plan via topological sort
Capability Synthesizer Creates novel capabilities from cognitive operators when no seed matches
Cognitive Substrate Operators and edges spanning all domains. Queryable reasoning graph.
Autonomy Calculator Risk and confidence analysis to determine human oversight level
Orchestrator Multi-agent dispatch with parallel execution and Capsule-sealed decisions
Checkpoint Manager Human approval gates with async wait patterns for high-risk operations
Adaptation Engine Signal capture, pattern mining, and safety-validated self-improvement
Drift Detector Behavioral consistency monitoring via cosine distance on embedding fingerprints

4 hardcoded safety constraints:

  1. HIGH-risk tasks (deploy, delete, decision) never auto-approved. Hardcoded, not configurable.
  2. Security agents (auditor, deployer) never receive prompt modifications from the adaptation engine.
  3. Injection patterns (shell, SQL, path traversal, secret leakage) blocked at the safety gate.
  4. Kill switch checked on every agent iteration. Once killed, stays killed.

Conduit: Internal Infrastructure

One command registers a service with DNS + TLS + reverse proxy routing.

  • Auto-DNS via dnsmasq for internal name resolution
  • Ed25519 TLS certificates from an internal Caddy CA
  • GPU monitoring (utilization, memory, temperature, processes)
  • Health checks with structured JSON audit logging
  • Admin dashboard with 6 views
  • Air-gap compatible. No internet required.

Tunnel: Secure Boundary

Double-encrypted remote access to any device, from anywhere.

Dual encryption:

Layer Protocol Algorithms
Outer WireGuard X25519, ChaCha20-Poly1305
Inner PQ-Hybrid TLS 1.3 X25519MLKEM768 (post-quantum key exchange)
  • 57 concurrent services supported
  • Split-tunnel routing
  • QR codes for mobile peer onboarding
  • Instant key revocation (no grace period)
  • 9 CLI commands for relay setup, peer management, key rotation, service exposure

Conduit handles the inside (service mesh). Tunnel handles the outside (remote access). Together they form a complete air-gapped networking layer.

capsule-litellm: LLM Audit Bridge

One line of code wraps every LLM call with a cryptographic audit trail:

import litellm
from capsule_litellm import CapsuleLogger

litellm.callbacks = [CapsuleLogger()]

# Every litellm.completion() now seals a Capsule with:
# - Model selection and provider
# - Prompt hash (SHA3-256, not the full prompt)
# - Token counts (input, output, total)
# - Duration and latency
# - Errors and retries

Works with any provider LiteLLM supports: OpenAI, Anthropic, Ollama, vLLM, NVIDIA NIMs, and 100+ more.


Architecture

How Packages Compose

                    ┌─────────────┐
                    │   capsule   │  <-- Foundation (zero dependencies)
                    └──────┬──────┘
                           |
              ┌────────────┼────────────┐
              |            |            |
        ┌─────v─────┐     |      ┌────v──────┐
        │   vault    │     |      │ conductor │
        └────────────┘     |      └───────────┘
                           |
                    ┌──────v──────┐
                    │capsule-litellm│
                    └─────────────┘

  Infrastructure (independent, pairs together):
  ┌──────────────┐  ┌──────────────┐
  │   conduit    │  │    tunnel    │
  │  (inside)    │  │  (outside)   │
  └──────────────┘  └──────────────┘

  Cross-language:
  ┌──────────────┐
  │  capsule-go  │  (Go verifier, stdlib only)
  └──────────────┘

Every package optionally depends on Capsule for audit trails. Each package works independently.

Cryptographic Standards

Operation Algorithm Standard
Content hashing SHA3-256 FIPS 202
Digital signatures Ed25519 RFC 8032
Post-quantum signatures ML-DSA-65 FIPS 204
Post-quantum key exchange X25519 + ML-KEM-768 RFC 7748 + FIPS 203
Symmetric encryption AES-256-GCM FIPS 197
Password hashing Argon2id RFC 9106

Never used: RSA, ECDSA P-256, MD5, SHA1, DES, 3DES, RC4.

Three Properties of Trustworthy AI

Every package is designed around three guarantees:

  1. Verified -- claims are checked against sources (Vault integrity checks, Conductor verification)
  2. Recorded -- every action creates a cryptographically sealed Capsule (forall action: exists capsule)
  3. Controllable -- any agent can be stopped instantly (Kill Switch: SOFT for graceful shutdown, HARD for immediate termination, cannot be disabled)

Compliance

Quantum Pipes maps to 11 regulatory frameworks:

Framework Scope Key Mapping
SOC 2 Trust Services Criteria Capsule audit trail satisfies CC6, CC7, CC8
HIPAA Healthcare data protection Vault data classification + Capsule access logging
GDPR EU data privacy Data sovereignty (zero egress) + right-to-erasure support
NIST AI RMF AI risk management Conductor autonomy levels + Capsule reasoning records
EU AI Act European AI regulation Pre-execution reasoning capture + human oversight gates
FedRAMP Federal cloud security Air-gap deployment + post-quantum cryptography
NIST SP 800-53 Federal security controls Kill Switch (SI-17), Capsule (AU-2, AU-3, AU-10)
ISO 27001 Information security management Vault trust tiers + Capsule chain integrity
CMMC DoD cybersecurity maturity Zero egress + cryptographic audit + network isolation
FINRA Financial industry regulation Capsule immutability + Vault record retention
PCI DSS Payment card data security Vault data classification + encryption at rest

Documentation

Pick a path based on what you need:

System design: how packages compose, the trust model, dependency graph, cryptographic standards.

Narrative walkthroughs explaining concepts from first principles: what Quantum Pipes is, the philosophy behind it, and deep dives into each major capability.

Per-package documentation: architecture, API reference, configuration, and integration patterns.

Regulatory framework mappings: how Quantum Pipes satisfies SOC 2, HIPAA, GDPR, NIST AI RMF, EU AI Act, FedRAMP, and more.

API reference, CLI reference, and configuration reference.

Security model, threat analysis, vulnerability disclosure policy, and cryptographic design rationale.

Complete, runnable examples demonstrating common integration patterns.


Contributing

See CONTRIBUTING.md for guidelines on contributing to Quantum Pipes documentation and code.

Security

To report vulnerabilities, see SECURITY.md. Do not open public issues for security concerns.

License

All Quantum Pipes packages are licensed under Apache-2.0.

Copyright 2024-2026 Quantum Pipes Technologies, LLC.

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Official documentation for the Quantum Pipes ecosystem. Offline-first AI with cryptographic accountability.

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