Intergrax

Intergrax helps teams build specialized AI applications that use controlled knowledge and tools while keeping access, actions, and evidence reviewable.

It is a reusable governed foundation—an application operating layer around execution boundaries—so product teams do not rebuild policy, approvals, integrations, recovery, and evidence mechanisms for every workflow.

Local Knowledge Workspace (LKW) is a private, governed AI knowledge workspace with Slack as its primary daily-use conversational interface for LKW 1.0. Add approved sources, ask over indexed knowledge from Slack or other supported clients, and inspect grounded answers with source references and persisted evidence. Reusable LKW HTTP and application APIs remain the backend boundary — Slack is the familiar work-surface direction, not the only client. A bounded Slack DM Ask path is live-verified today; the broader Slack-first daily-use experience remains under productization.

Python 3.12 Source-available Active R&D Documented proof paths

See LKW · Run LKW locally · Why Intergrax

Intergrax is source-available and under active R&D. LKW is a Backend Product Alpha / MVP. Real-user validation and commercial validation are incomplete.


Choose your path

If you are… Start here What this gives you
AI Engineer / Builder Builder Quick Start Build a runnable agent + application stack
Architect / Principal Engineer Architecture Overview Understand responsibilities, boundaries, and system design
CTO / Engineering Leader Use Cases Decide whether Intergrax fits a concrete workflow
Technical Reviewer PROOFS Inspect what is actually implemented / boundedly proven
Investor / Strategic Evaluator Why Intergrax Understand the platform thesis, LKW wedge, and open validation gates
Design Partner / Integrator Partners Explore a bounded evaluation or pilot around a concrete workflow

Looking for configuration, evaluation guidance, roadmap, collaboration, permissions, capability-specific material, or deeper technical documentation? Explore the Public Documentation Map.

Questions? See the FAQ.


Local Knowledge Workspace (LKW)

Product workflow

approved knowledge
→ LKW workspace
→ ask from Slack / supported client
→ grounded answer
→ sources / persisted evidence

Product Quick Start is the easiest supported local executable proof path: indexed Ask V1 over a bundled sample document (AURORA-17 is the expected success marker). It does not require Slack setup.

Slack is the primary daily-use conversational interface direction for LKW 1.0. A bounded DM Ask path is live-verified today; broader Slack workspace, source-management, and daily-use flows remain under productization.

This visual represents the documented Quick Start, not a finished UI screenshot; dynamic workspace and Ask-run IDs are omitted.

What is boundedly proven today

LKW is the Primary Product Proof, classified as Backend Product Alpha / MVP, with PARTIAL status.

Primary executable product path: Product Quick Start exercises indexed Ask V1 — not Hybrid Ask certification, Trusted Ask durability, or Core Platform Proof.

Separate bounded technical evidence: indexed Hybrid Ask branch (LKW-HYBRID-ASK-INDEXED) is a real application code path for indexed retrieval. Hybrid Ask combining indexed and authorized live evidence is not yet proven.

Separate live durability evidence: Trusted Ask (LKW-ASK-WORKSPACE-LIVE) verifies completed grounded Ask outcomes across restart without resync/reindex.

Not yet proven: complete live-provider access, finished end-user packaging, real-user validation, and commercial validation. See LKW Platform Proof and PROOFS.

Try LKW

One supported command takes you from the repository root to a grounded answer with a source citation over indexed knowledge — the canonical Product Quick Start path, separate from Slack DM setup. Detailed prerequisites and troubleshooting live in the LKW Quick Start.

Windows:

applications\local_workspace_application\scripts\run-lkw-product-quickstart-windows.bat

Linux:

./applications/local_workspace_application/scripts/run-lkw-product-quickstart-linux.sh

macOS:

./applications/local_workspace_application/scripts/run-lkw-product-quickstart-macos.sh

Expected answer marker: AURORA-17 · Expected source file: lkw_product_quickstart.txt

First run may download Docker images and configured models when Ollama is the selected provider; duration depends on your environment.

LKW routes

Route Purpose
Product Tour Understand what the product experience looks like
Quick Start Run the canonical product path
Core Platform Proof Verify bounded infrastructure/platform behavior

Core Platform Proof is separate from Product Quick Start and Trusted Ask: a platform-level bounded proof covering startup/readiness, durable knowledge and execution, background processing, persisted reviewable evidence, hosting/recovery, and watched-folder indexing — not production readiness, commercial validation, or all-provider certification.

Proof families: Product evaluation (LKW-PRODUCT-QUICKSTART-*), Core platform (LKW-BACKGROUND-TASK, LKW-HOSTING, LKW-FILE-WATCHER), Indexed Hybrid Ask (LKW-HYBRID-ASK-INDEXED), Trusted Ask (LKW-ASK-WORKSPACE-LIVE).


Why this matters

Building an impressive AI demo is easier than operating a controlled AI application that a team can review and trust. Teams repeatedly rebuild knowledge access, policy, integrations, approvals, and evidence foundations around each product.

Intergrax centralizes reusable mechanisms so product teams can focus on the specialized workflow. Read Why Intergrax for the category, problem, and fit.

Responsibility model

The root-level model is about responsibility, not a mandatory execution sequence. A request uses only the configured resources its product context selects.

Responsibility What it owns
Specialized product application Product workflow, UX, business semantics, permissions, and acceptance
Intergrax Reusable application operating layer for policy and approval boundaries, controlled context, governed execution, recovery, observability, and evidence / provenance
Model / agent Reasoning, inference, and decision generation within supplied context and governed boundaries
Knowledge / tools / integrations / models Selected resources behind configured access and effect boundaries
Evidence / provenance Reviewable receipts, traces, and records produced during execution

See the Architecture Overview for the complete responsibility model.

AI execution should not be a black box

Meaningful AI execution should be reconstructable, reviewable, and attributable. Intergrax is designed so important actions do not disappear inside an opaque agent loop.

request → context → agent / plan / decision → policy / approval
       → model / RAG / tool → validation → result → evidence
                              ↓
                 reviewable execution record

A governed run can leave correlated runtime events, typed DecisionRecord artifacts, and structured ProofReceipt evidence. This is execution-level explainability, not hidden model reasoning. Universal every-path production observability is not claimed.

Observability · Reasoning / DecisionRecord · Proof Receipts

Runnable evidence: Inspect the current bounded LKW observability proof, including independently inspectable Elasticsearch/Kibana records, controlled Sentry problem signals, and persisted execution evidence. LKW bounded observability proof · Controlled Sentry proof

What exists today

Status is capability-specific; implementation is not blanket proof of the whole platform.

Area Role Current status
LKW Primary Product Proof PARTIAL — Backend Product Alpha / MVP
Other reusable foundations Supporting evidence Varies by capability; inspect PROOFS

Platform capability maturity is summarized in Platform capabilities and directions below.

Platform capabilities and directions

Compact index of strategic platform capabilities. Status is bounded and capability-specific; see linked architecture and proof routes for detail.

Capability / direction What it adds Current maturity Explore
Governed Execution Reusable policy and approval enforcement around agent decisions, tool/action boundaries and meaningful side effects, with canonical HITL and plugin-extensible policy rules IMPLEMENTED SLICES — consolidation / qualification ongoing — complete platform-wide governance and production qualification not established Governed Execution
Observability & Auditability Shared observability spine for reconstructable, reviewable governed execution — runtime events, DecisionRecord artifacts, ProofReceipt evidence; execution-level explainability, not hidden chain-of-thought IMPLEMENTED CORE + BOUNDED PROOF — universal every-path production observability not claimed Observability · LKW bounded observability proof · Controlled Sentry proof
Token Optimization Featured platform-capability proof — policy-governed context and prompt optimization with receipts, fallback, and bounded offline proof PARTIAL — bounded — universal savings and production-proven savings not established Token Optimization guide · Claim guardrails
Multiplayer AI Governed multi-principal collaboration among humans, agents, services, and external agents Architecture / roadmap stage — runtime proof not yet established Multiplayer AI architecture
Platform Extensibility Governed extension/package model across domain-owned contracts Canonical architecture frozen — implementation stages planned; complete third-party install-to-runtime E2E proof not yet established Platform Plugins
Agent Marketplace Future ecosystem layer — discovery and distribution over governed Agent Distribution / Platform Extensibility FUTURE PRODUCT — NOT SHIPPED TODAY Agent Marketplace concept

License and collaboration

Intergrax is source-available under the Intergrax Evaluation and Collaboration License 1.0. You may clone, install, run, test, and modify the repository locally for non-production evaluation, subject to the LICENSE.

Feedback, contribution, permission, and pilot routes are described in Collaboration and Partners. Production use, commercial use, hosting, and redistribution require explicit written permission or agreement under the legally authoritative LICENSE.