BHANUJBHANUJ
v1.2.2

Overview

BHANUJ AIGP helps you keep a clear record of how your AI system works, check important changes, and make rules about what is allowed. Your application still runs where it does today.

Think of AIGP as a notebook and safety check for your AI system. It records the prompts, models, data, and runs you choose to track. It can compare results, apply rules, and show why it made a decision. It does not run your models, publish your prompts, or replace your deployment tools.

Your systems keep doing the AI work. BHANUJ AIGP records the important parts, checks them against rules you set, and saves the reason for each result. That gives your team a reliable history to review later.

Latest Release

The current release expands the control plane with governed evaluation inputs, runtime evidence, and safe execution-level review. It adds:

  • Managed, immutable prompt and model versions alongside observed runtime assets.
  • Managed dataset lifecycle controls and consistent-dataset candidate comparisons.
  • Tenant-scoped Runtime Connections and validated provider/model capability profiles.
  • Candidate execution evidence, per-item evaluation results, cancellation, and progress visibility.
  • A first-class Policy Engine with version lifecycle, simulation, condition traces, and explainable decisions.
  • Agents Runtime evidence for externally run agents, including ordered execution timelines and deterministic operational findings.
  • Causal Audit for safe, isolated checks of whether approved tool evidence materially affected a measured outcome.

Start with Asset Catalogs, the Evaluation Engine, and the Policy Engine for the detailed contracts and operational boundaries.

Architectural Planes

The system is organized into independent planes. Each plane owns a single responsibility and communicates only through explicit contracts:

  • Audit Plane — captures workflow and node-level execution records for reconstruction and investigation.
  • Replay Plane — reconstructs historical executions from persisted audit state. It replays ordered Agent Runtime events, keeping action sequence, failures and recovery inspectable. Unsupported conclusions fail closed.
  • Evaluation Plane — turns workflow outputs into evaluation results using pluggable providers. It compares models and agent scaffolds under versioned conditions, with item-level metrics and immutable runner provenance.
  • Job Execution Plane — records and executes long-running governance work with durable lifecycle tracking.
  • Persistence Plane — stores governed artifacts through replaceable repository contracts.
  • Asset Plane — catalogs versioned prompts, models, datasets, and evaluation providers with explicit ownership and ontology-backed lineage.
  • History Plane — retrieves and organizes evaluations into history views, trends, and comparisons.
  • Governance Plane — analyzes change over time, calculates drift, and produces governance-oriented artifacts.
  • Policy Engine — evaluates versioned, structured rules against captured evidence and persists explainable governance outcomes.
  • Agents Runtime — records bounded evidence from externally run agents and identifies deterministic operational conditions for review.
  • Causal Audit — uses an approved, isolated replay to measure whether specific tool evidence materially affected an eligible outcome.
  • Governance Ontology Plane — semantic graph describing relationships between governed assets.
  • Settings Control Plane — typed configuration with SYSTEM, ORGANIZATION and PROJECT scopes.

See the architecture overview for a full breakdown of each plane and how they interact.

Policy Engine

The Policy Engine turns evidence into repeatable governance decisions. Policies are versioned and target governed entities such as experiment candidates, prompt versions, and model versions. Their rules have explicit priorities, conditions, effects, and reasons; the resulting decision preserves the matching rule, condition trace, evidence, explanation, and audit context.

Read the Policy Engine guide to understand rule authoring, simulation, lifecycle, outcome precedence, and decision review.

Interfaces

Every governance operation is available over a versioned REST API and as an auditable MCP tool. The MCP server exposes governed read and controlled-write operations to agents, while the REST APIs serve consoles, CLIs and service-to-service integrations.

Extensibility

AIGP exposes a versioned extension surface for independently released integrations. Plugins can add routes, providers, lifecycle hooks, and event subscribers through declared contracts; they do not modify AIGP source or depend on internal services.

This keeps the OSS control plane authoritative while allowing future commercial or organization-specific packages to evolve independently. Read the Extensibility guide for plugin lifecycle, compatibility, and operational rules.

Where to start