---
updatedAt: 2026-10-07T16:26:49.000Z
agentTools:
  projectIndex: https://documentation.picsellia.com/llms.txt
---

# Inferences

Until now, the different features related to a `Deployment` have been described. So you should now have a fully and properly configured `Deployment`. It is then, high time to log the result of inferences in it.

The `ModelVersion` that is related to the current `Deployment` can be deployed either:

* [On the *Picsellia Serving Engine*](https://documentation.picsellia.com/docs/registry-deploy-a-model#a-picsellia-serving)
* [On your own serving infrastructure](https://documentation.picsellia.com/docs/registry-deploy-a-model#b-monitoring-only)

## 1. If the `ModelVersion` is deployed on *Picsellia Serving Engine*

If the `ModelVersion` is deployed on the *Picsellia Serving Engine*, you need to use the *Picsellia Python SDK* to make this `ModelVersion` make inferences on your image.

Here is the recipe to follow to make your `ModelVersion` deployed on the *Picsellia Serving Engine* doing an inference:

<TutorialTile backgroundColor="#f4df01" emoji="⛳" id="676546a0efe0220036181a74" link="https://documentation.picsellia.com/v3.0/recipes/make-predictions" slug="make-predictions" title="Make predictions" />

The fact that the `ModelVersion` is deployed on *Picsellia Serving Engine* is quite convenient as when the inference is done, the `PredictedAsset` and associated `Prediction` are automatically and properly logged by Picsellia on the associated `Deployment`.

You can then visualize the `PredictedAsset` and associated `Prediction` using the *[Predictions overview](https://documentation.picsellia.com/docs/deployments-predictions-overview)* and [perform *Reviews* using the *Prediciton Review tool*](https://documentation.picsellia.com/docs/deployments-predictions-review) for instance.

## 2. If the `ModelVersion` is deployed on your own serving infrastructure

If the `ModelVersion` is deployed on your own serving infrastructure you are in charge of making your `ModelVersion` infer properly. In addition, you will have to adapt the script that is performing the inference on your infrastructure to make it log the result of the inference (i.e. the `PredictedAsset` and the associated `Prediction`).

[Here](https://documentation.picsellia.com/docs/monitoring-an-external-model) is the procedure to apply to log the result of your inference on a dedicated Picsellia `Deployment`.

Once logged, you can then visualize the `PredictedAsset` and associated `Prediction` using the *[Predictions overview](https://documentation.picsellia.com/docs/deployments-predictions-overview)* and [perform *Reviews* using the *Prediciton Review tool*](https://documentation.picsellia.com/docs/deployments-predictions-review) for instance.