Getting Started

Overview

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AISquare is an audit, trust, and governance infrastructure for agentic systems.

It enables organizations to observe, explain, and control AI agent decisions, making them safe, defensible, and ready for enterprise deployment.

Why AISquare exists

As organizations adopt AI agents, a critical challenge emerges:

AI systems make decisions that cannot be easily explained, audited, or trusted.

This creates three major risks:

  • Regulatory risk → no audit trail for AI decisions
  • Legal risk → inability to explain outcomes
  • Reputational risk → black-box failures becoming public

Without governance, AI adoption slows down or stops entirely.

What AISquare does

AISquare introduces a missing layer in modern AI systems: a system of record for AI decisions.

Just like:

  • Financial systems track transactions
  • HR systems track people

AISquare tracks and governs AI decision-making.

Core capabilities

AISquare provides a complete governance layer for AI agents.

Durable decision record

A tamper-evident log of every agent action and reasoning path. This ensures decisions can be audited and defended when needed.

Human-in-the-loop governance

Structured workflows allow humans to review, approve, or intervene in agent decisions.

Decision-level policy enforcement

Policies can be applied directly to agent reasoning to:

  • Allow
  • Deny
  • Escalate
  • Modify decisions

No-code audit interface

Non-technical users can inspect and replay decisions without engineering support.

How AISquare works

AISquare integrates into your existing AI systems and provides visibility into how decisions are made.

A typical flow:

  1. Connect your agents — Integrate agents from any framework using AISquare SDK
  2. Navigate decisions — Visualize decision flows and reasoning paths
  3. Audit reasoning — Understand claims, assumptions, and evidence
  4. Apply policies — Add human feedback and governance controls

The reasoning and memory graph

At the core of AISquare is a persistent reasoning graph.

This graph:

  • Records why decisions are made
  • Preserves logic and context
  • Stores human interventions
  • Acts as audit-ready evidence

It turns AI decision-making into a traceable, durable artifact.

What you can build

AISquare works with any:

  • AI framework
  • Model
  • Workflow

You can:

  • Build agents internally
  • Work with partners
  • Deploy using AISquare

AISquare ensures every agent is:

  • Auditable
  • Explainable
  • Governed
  • Scalable

Why developers use AISquare

AISquare helps teams:

  • Ship AI agents faster
  • Debug and optimize decision flows
  • Reduce risk with policy controls
  • Deliver enterprise-grade AI systems

It enables teams to move from experimental agents to production-ready systems.

What this API enables

The AISquare API allows you to:

  • Retrieve and analyze agent decisions
  • Access structured experience and resource data
  • Manage collections and workflows
  • Build applications on top of governed AI systems

Next steps

To get started: