Invarcore
SYSTEMS VERIFIED
GitHub
STANDALONE UTILITIES · ZERO-TRUST SECURITY · APPLIED AI

Deterministic Invariants for
Modern AI Systems

Invarcore builds high-performance developer tools, zero-trust runtime guardrails, and applied intelligence applications. Adopt standalone drop-in utilities to cut costs and debug agents, or deploy the unified verification fabric for enterprise defense.

Explore All Innovations View Source on GitHub
80%
KV-Cache Cost Reduction
Powered by cachealign
< 1ms
Circuit Breaker Trip Time
Powered by canary-fabric
100%
Deterministic Offline CI
Two-tier golden fixtures
< 2ms
SQLite WAL Trajectory Overhead
Powered by unloop
Strategic Value Alignment

Built for the Entire Technical Organization

Whether you manage financial risk, design user experiences, architect enterprise infrastructure, or write Python code, Invarcore solves the hardest failure modes of autonomous AI.

FOR CEOS, CFOS & CHIEF RISK OFFICERS

Protect Enterprise Capital, Eliminate Liability & Cut LLM Spend by 80%

Generative AI introduces severe existential risks: confidential IP exfiltration, uncontrolled cloud invoices, and compliance penalties under the EU AI Act and NIST standards. Invarcore gives business leaders quantifiable financial ROI and fail-closed legal defense.

Enterprise Transformation

The Invariant Difference

Replace stochastic uncertainty and fragile prompt guardrails with mathematical invariants and wire-level verification.

Without Invarcore: Stochastic Drift

Unbounded Vulnerability & Waste

  • ✕ Silent Data Exfiltration: Proprietary enterprise knowledge and PII leak undetected into egress LLM streaming responses.
  • ✕ Hallucinated Write Actions: Agents given API tokens execute unverified database modifications without cryptographic sign-off.
  • ✕ Runaway Cloud Invoices: Shifting prompt prefixes bypass LLM KV-caching, causing 5x inflated API bills.
  • ✕ Infinite Critique Loops: Agents get stuck in self-doubt retry cycles, burning compute without human or watchdog intervention.
With Invarcore: Mathematical Invariants

Deterministic Certainty & Control

  • ✓ Sub-Millisecond Circuit Breakers: Invisible steganographic tokens sever compromised streams before data can escape.
  • ✓ Cryptographic Non-Repudiation: Ed25519 & HMAC-SHA256 signatures guarantee that no action commits without policy authorization.
  • ✓ 80% Cache Cost Reduction: Autonomous prefix alignment middleware stabilizes prompt prefixes for maximum KV-cache reuse.
  • ✓ Time-Travel Debugging: Watchdogs monitor trajectory convergence, rewinding turns with state mutations to break deadlocks.
Product Ecosystem

Standalone Innovations & Integrated Suites

Every Invarcore product delivers immediate, independent value out of the box, with native cross-compatibility when deployed together.

Standalone Drop-In MIT License
⚡

cachealign

Autonomous prompt cache optimizer & prefix alignment proxy middleware. Cuts LLM inference costs and API token bills by up to 80% without modifying your application code.

Invariant: Prefix stability is preserved across multi-turn agent sessions.
  • ✓ Drop-in reverse proxy compatible with OpenAI, Anthropic, and vLLM
  • ✓ Autonomous turn reordering & prompt header stabilization
  • ✓ Up to 3x reduction in Time to First Token (TTFT)
Python · Proxy · Redis/Memory github.com/invarcore/cachealign →
Standalone DevTool MIT License
⏪

unloop

The time-travel debugger for AI agents. Pause agents mid-thought, rewind cognitive turns like a video player, and break out of infinite critique/retry loops in-flight.

Invariant: Agent cognitive trajectories must terminate deterministically.
  • ✓ Ultra-fast SQLite WAL trajectory persistence (<2ms write tax)
  • ✓ OscillationWatchdog convergence monitoring and loop interception
  • ✓ Terminal UI and MCP inspector toolset for interactive debugging
Python · SQLite WAL · Terminal UI · FastMCP github.com/invarcore/unloop →
Verification Fabric Suite Apache 2.0
🛡️

canary-fabric

Invisible steganographic tripwires and sub-millisecond data-leak circuit breakers. Watermarks retrieval chunks and severs compromised egress streams in real-time.

Invariant: Zero unmonitored data exfiltration in RAG pipelines.
  • ✓ Steganographic zero-width cryptographic token injection
  • ✓ SlidingWindowStreamBuffer for live LLM streaming output
  • ✓ 0.78ms fail-closed circuit breaker severance latency
Python · FastMCP · Steganography · HMAC github.com/invarcore/canary-fabric →
Verification Fabric Suite Apache 2.0
⚖️

intent-fabric

Policy-governed autonomous agent planning framework. Synthesizes multi-turn plans from evidence, dry-runs constraints, and requires cryptographic signatures before write execution.

Invariant: No state-mutating action executes without a verified signature.
  • ✓ Multi-turn action synthesis from grounded evidence packages
  • ✓ Pre-flight policy dry-run simulation against YAML constraints
  • ✓ HMAC-SHA256 & Ed25519 approval package non-repudiation contracts
Python · Pydantic · Ed25519 · OpenRouter github.com/invarcore/intent-fabric →
Verification Fabric Suite Apache 2.0
🧠

knowledge-fabric

MCP-native hybrid evidence retrieval platform. Combines pgvector semantic search with BM25 full-text indexing via Reciprocal Rank Fusion into cryptographically digested packages.

Invariant: All generated answers must be grounded in digested evidence.
  • ✓ Structure-preserving chunking for technical specifications and code
  • ✓ Native Model Context Protocol (FastMCP) server implementation
  • ✓ Cryptographically hashed EvidencePackages with verifiable provenance
Python · PostgreSQL · pgvector · FastMCP github.com/invarcore/knowledge-fabric →
Verification Fabric Suite Apache 2.0
📚

enterprise-adapters

Fail-closed SaaS document ingestion connectors for Confluence, Jira, and Notion. Scrubs private credentials and PII via automated DLP filters before vectorization.

Invariant: PII and enterprise secrets never enter vector embeddings.
  • ✓ High-speed regex DLP scrubbing (AWS keys, JWTs, private keys)
  • ✓ Strict rate-limit governance and exponential backoff handling
  • ✓ Cryptographic action verification before committing write actions
Python · Confluence / Jira / Notion APIs github.com/invarcore/...adapters →
Applied Application Browser Extension
🗡️

PitchBlade AI

The high-signal proposal intelligence assistant & Connects ROI radar. Mines client reviews to extract real names, scores job quality to prevent burned tokens, and crafts 2-line diagnostic hooks.

Invariant: Never spend resources on unverified, low-signal job postings.
  • ✓ Red-Flag Radar: Audits hire rates and spend history before bidding
  • ✓ Client Name Hunter: Mines historical reviews to personalize greetings
  • ✓ 100% Client-side assistive overlay (zero bot ban risk)
Chrome Extension · Manifest V3 · TypeScript In Pipeline / Prototyping
Invarcore Labs R&D Roadmap
🔬

Active Labs Pipeline

High-conviction architectural innovations advancing from research blueprints to open-source prototypes.

Upcoming: Fault-injection, local speculative acceleration & vector privacy.
  • ✦ AgentChaos: Chaos engineering test harness for tool failure simulation
  • ✦ asym-spec: Asymmetric speculative decoding running 70B models 3x faster on local NPUs
  • ✦ BlindVector: Mathematical embedding rotation for multi-tenant vector privacy
Exploration Tracker · High Conviction Research Blueprint
Integrated Verification Fabric

How the Engines Synergize Together

When combined, Invarcore security engines form an unbroken chain of custody from raw SaaS data ingestion to supervised agent execution. Click any stage to inspect its contract.

STAGE 01

SaaS Ingestion

DLP Secret Scrubbing
STAGE 02

Evidence Pack

Hybrid RRF Vector
STAGE 03

Canary Tripwire

Steganography
STAGE 04

Cache Alignment

Prefix Stability
STAGE 05

Intent Sign-off

HMAC / Ed25519
STAGE 06

Time-Travel

Anti-Oscillation

1. Enterprise SaaS Ingestion

Engine: knowledge-fabric-enterprise-adapters
Guaranteed Invariant: "PII, AWS secrets, and enterprise credentials never touch vector embeddings."

Fail-closed connectors for Jira, Confluence, and Notion. Scrapes document bodies, scrubs private credentials via high-speed regex DLP filters, and enforces rate-limiting backoffs before emitting document streams.

Inspect knowledge-fabric-enterprise-adapters on GitHub →
Formal Methods & Applied Research

Technical Whitepapers & Invariant Specifications

Mathematical proofs, cryptographic protocols, and systems telemetry underpinning the Invarcore verification fabric.

INV-WP-2026-01 Inference Systems March 2026

Deterministic Prefix Stabilization: Formal Invariants for High-Entropy Prompt Cache Reuse in Multi-Turn Agent Trajectories

Invarcore Systems Architecture Group · Ref: cachealign

Multi-turn autonomous agents frequently perturb token prefixes via non-deterministic tool declarations and dynamic timestamps, triggering full KV-cache invalidation in PagedAttention runtimes. We formalize deterministic prefix stabilization, achieving ≥82.4% KV-cache block hit rates and reducing Time to First Token (TTFT) by 68.2%.

MATHEMATICAL INVARIANT: ∀ t ∈ [1, T],   LCP(τt, τt-1) ≥ |Prefix| &implies; CacheHit(Block0..m) ≡ 1
INV-WP-2026-02 Data Loss Prevention February 2026

Steganographic Zero-Width Canary Tripwires: Wire-Level Egress Interception for Enterprise RAG Runtimes

Invarcore Applied Security Research Group · Ref: canary-fabric

Synchronous DLP passes add unacceptable TTFT latency (150–2000ms) to streaming RAG applications. We formulate a 4-ary zero-width steganographic watermarking protocol with binomial statistical significance testing (p < 10⁻⁴) and a lookahead stream buffer severing compromised sockets in <0.8ms.

MATHEMATICAL INVARIANT: Pr(CanaryExfiltration ∧ ¬CircuitTrip) < 10⁻⁶,   LatencyOverhead < 0.8ms
INV-WP-2026-03 Agent Convergence January 2026

Vector Entropy Trajectory Analysis: Non-Oscillation Invariants for Autonomous Agent Multi-Turn Loops

Invarcore Applied Intelligence Group · Ref: unloop

Autonomous agent trajectories subjected to multi-step reasoning often collapse into cyclic deadlock attractors. We introduce trajectory state-space tracking via sliding-window cosine similarity and Shannon vector entropy, detecting cognitive loops and executing deterministic state rewinds via SQLite WAL snapshots.

MATHEMATICAL INVARIANT: lim(t→∞) St ∈ Sterminal   where   ∮ dH ≠ 0 &implies; Rollback(St-Δt)
INV-WP-2026-04 Cryptographic Policy February 2026

Formal Intent Contracts: Mathematical Non-Repudiation for Autonomous State Mutations

Invarcore Systems Architecture Group · Ref: intent-fabric

Direct tool invocation by LLMs creates severe injection vulnerabilities. We formalize Intent Contracts, decoupling unconstrained reasoning from action execution via Ed25519/HMAC-SHA256 signed policy envelopes. Mutations execute if and only if cryptographic assertions and dry-run AST predicates pass.

MATHEMATICAL INVARIANT: Execute(a) ⇔ VerifyEd25519(a, σ, pk) ∧ Precondition(a, Spre) ∧ Policy(ΔS) ≡ True
INV-WP-2026-05 Embedding Governance January 2026

Fail-Closed Knowledge Ingestion: Structure-Preserving Chunking & Zero-Leak Redaction for Vector Embeddings

Invarcore Applied Security Research Group · Ref: knowledge-fabric

Standard RAG ingestion irreversibly projects private API keys and customer PII into vector embeddings. We formalize fail-closed ingestion boundaries with AST-preserving Markdown parsers and pre-vectorization regex/entropy redaction, ensuring tabular hierarchy integrity and zero credential leakage.

MATHEMATICAL INVARIANT: ∀ c ∈ C,   Entropy(c) < Hsecret ∧ ASTvalid(c) &implies; Embedding(c) ∩ Secrets ≡ ∅
Institutional Rigor

Built for Enterprise Compliance

Security is built into our software supply chain. Every repository adheres to verifiable DevSecOps baselines.

✓

Two-Tier Test Isolation

100% of unit test suites run offline using checked-in golden fixtures. CI builds never fail due to external DNS timeouts or rate limits.

✓

Push Protection & Secret Scanning

Wire-level push protection blocks any commit containing API keys, private tokens, or certificates before reaching remote git servers.

✓

Fail-Closed Default State

If a policy verification timeout, canary anomaly, or credential check fails, execution envelopes halt immediately rather than failing open.

✓

≥90% Mandatory Coverage

Every engine maintains rigorous unit and edge-case coverage metrics verified by automated GitHub Actions CI matrices across Python 3.10–3.12.

Coordinated Vulnerability Disclosure (CVD)

We partner with security researchers and enterprise teams to resolve vulnerabilities safely and transparently. Invarcore commits to an initial response within 24–48 hours for all private security advisories.

Report to security@invarcore.com