> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Task handover (early access)

> Early access: move each task to your own AI only after it passes a test, move it back if quality slips, and keep a record your regulator can check.

> [!NOTE]
>
> The open-source framework is live today. The handover is in early access, and we are taking on our first design partners. [Talk to us about early access](https://praison.ai/enterprise/).

Each task moves to your own AI only after it passes a test. If quality slips, it moves back automatically, and every step is recorded for regulators.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    W[Watch] --> T[Test]
    T --> H{Passes?}
    H -->|yes| O[Hand over<br/>to your own AI]
    H -->|not yet| W
    O --> Q{Quality holds?}
    Q -->|yes| O
    Q -->|no| B[Roll back]
    B --> W
    W -.-> R[(Record)]
    T -.-> R
    O -.-> R
    B -.-> R

    classDef agent fill:#8B0000,color:#fff
    classDef tool fill:#189AB4,color:#fff

    class W,T,O,B agent
    class H,Q,R tool
```

## How it works

1. **Watch:** records how each task is done today.
2. **Test:** turns that real work into tests.
3. **Hand over:** a task moves to your own AI only when it passes.
4. **Roll back:** if quality drops, the task moves back automatically.
5. **Record:** every handover leaves a record your regulator can check.

## Who it is for

Banks, insurers and hospitals that want AI agents but cannot send private data to outside AI services. Keep your data inside, own your AI, and get proof for your regulators.

***

## What it builds on today

The handover is not part of the open-source packages. It is built on parts that are already in the open-source framework, which you can use now:

> [card] [Tracing](https://praison.ai/docs/observability/overview.md)
>
> Record what an agent did, step by step

> [card] [Evaluation with run\_trials](https://praison.ai/docs/features/trials-engine.md)
>
> Run each test case many times and get a pass rate

> [card] [Fine-tuning with praisonai-train](https://praison.ai/docs/features/praisonai-train-package.md)
>
> Train a model of your own on your own data

> [card] [Local models](https://praison.ai/docs/guides/run-fully-offline.md)
>
> Run agents fully offline on your own computers

> [card] [Model router](https://praison.ai/docs/features/model-router.md)
>
> Choose which model handles each task

> [card] [Local model servers](https://praison.ai/docs/features/local-models.md)
>
> Ollama, LM Studio, llama.cpp and vLLM

***

## Early access

We are taking on our first design partners. If you run a highly regulated team, such as a bank, insurer or hospital, and want to try the handover, [get in touch](https://praison.ai/enterprise/).

> [accordion] Is the handover available to install?
>
> No. It is in early access and is not part of `pip install praisonai`. Everything else on this site is open source and available today.

> [accordion] Can I build something like this myself?
>
> Yes. Tracing, evaluation, fine-tuning and local models are all in the open-source framework. The cards above link to each one.

> [accordion] Does this change the open-source framework?
>
> No. PraisonAI is still a general-purpose agent framework, and every feature works as before. See the [Introduction](https://praison.ai/docs/introduction.md).


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