> For the complete documentation index, see [llms.txt](https://docs.ai-interval.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ai-interval.com/platform-overview/harness.md).

# Harness

**Private AI: governed agent work inside your environment.**

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## Harness Framework

### Next-Generation AI Infrastructure

The **Harness** transforms how businesses use AI by bringing intelligence directly to your data without moving sensitive information outside your control. It addresses the critical decision point for traditional enterprises: how to harness artificial intelligence without compromising data security or requiring massive technical transformation.

* **Private Data Governance:** Data never leaves the premises and access is human-governed with granular controls. 
* **Private AI Inference**: Leverage Interval's on-premise, open source inference for highly privacy-strict workflows tailored for your business and cost-optimized.
* **Swappable Architecture:** Harness components are configurable so agent boundaries can shrink/expand as needed and allow you to bring your own models/providers or use local private AI inference.
* **Developer Enablement**: Developers can quickly ship integrated data applications with strict controls using the **Workbench.**

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## Harness Workbench

The Workbench is the interface and tooling ecosystem that joins governed data access, private AI models, explicit human control, and an auditable proof layer.

<figure><img src="https://3578782341-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fw5DD9KZvZ1mFMUA9o0HN%2Fuploads%2F8XTrIuJ52FgC6DXdOcUF%2Fimage.png?alt=media&amp;token=16e0c4c0-9f93-47f8-a5bc-44cee0b1d3b0" alt=""><figcaption></figcaption></figure>

This allows users to build applications directly embedding enriched data sources, gated by the same RBAC policies that govern Harvest data access across an organization.&#x20;

### Delivery Surfaces

The Workbench integrates with the Portal or any modern developer tool like Cursor or Pi-dev. A developer or even non-technical user can quickly build software using inherited user permissions and retain full control over their workflows.

### Control Graph

At its core, the Workbench defines a graph that allows for granular, configurable control flow per task. It allows the user to define when human intervention is a gate at any point in the build process. It also determines the coordination of specific, agentic tasks like adversarial review, fan-outs, and loops.

Each node in the graph is an individual stage-gate. Some nodes are deterministic, others are agent tasks.

### Agent Loadouts

For agent tasks, nodes are pre-determined loadouts that employ an adapter architecture. Each node runs in an ephemeral runtime with declared resource limits.

A swappable model is paired with governed context, permissions, tool use, and token budgets. This allows for the distinction between an early planning cycle using a powerful frontier model that doesn't have direct access to private data versus an execution cycle using a low-cost, local model that can access private data and make code changes.

<figure><img src="https://3578782341-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Fw5DD9KZvZ1mFMUA9o0HN%2Fuploads%2FbfoGwB9jWPETP0TU5PkO%2Fimage.png?alt=media&amp;token=b8254b52-4778-457f-abd2-b0227644a209" alt=""><figcaption></figcaption></figure>

### Proof Layer

Any and all actions performed by an agent or human are captured by audit logs that enable a proof layer - answering questions like:

* Who approved this workflow?
* What data was the AI granted access to?
* Where did some specific metric come from and what was the data lineage?

The Workbench integrates directly with Interval's core permissioning and audit primitives.