ceven

Roboflow

Triggers computer vision pipelines on new images, validates workflow schemas for accuracy, and monitors inference server health to ensure your visual AI stays online.

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Why use Ceven?

  1. AI native Roboflow integration

    • Describe the outcome and Ceven picks the right Roboflow calls, fills the parameters, and checks the result.
    • Structured, agent friendly tool schemas so each call runs reliably instead of by guesswork.
    • Rich coverage for reading, writing, and querying your Roboflow data, across all 7 of its actions.

  2. Managed auth

    • Built in OAuth with automatic token refresh and rotation.
    • One place to manage, scope, and revoke Roboflow access.
    • Per user and per environment credentials instead of shared keys.

  3. Agent optimized design

    • Actions are tuned from real success and error rates so reliability climbs over time.
    • Full execution logs so you always know what ran in Roboflow, when, and on whose behalf.
    • The agent pauses and asks when Roboflow is unclear instead of plowing ahead.

  4. Enterprise grade security

    • Fine grained access so you control which agents and people can reach Roboflow.
    • Least privilege by default, read scopes first and only the writes a workflow needs.
    • A full audit trail of every Roboflow action to support review and sign off.

Supported tools

Every action Ceven's agents can run on Roboflow, and when to use it.

Run Workflow
Use this to execute a custom Roboflow workflow pipeline for image processing or model inference.
Validate Workflow
Check if a workflow definition is syntactically correct and properly structured before you deploy it.
Describe Workflow Interface
Pull the inputs, outputs, and types for a specific Roboflow workflow specification.
Get Workflow Schema
Fetch the complete schema definition for workflow blocks to ensure compatibility.
Get Server Metrics
Pull Prometheus metrics from the inference server to track performance and health.
Get Server Info
Retrieve the server version, name, and unique identifier for the current inference host.
Get Execution Engine Versions
Check which execution engine versions are currently supported for workflow processing.

7 actions · scroll to see them all

Frequently asked questions

Ceven acts as a secure bridge between your image storage and the Roboflow inference server. When a workflow triggers, the agent fetches the image from your source, such as an S3 bucket or a local upload, and passes it to the Roboflow Run Workflow endpoint. We do not store the images on our own servers permanently. Once the inference server returns the object detection or segmentation results, the agent processes the JSON response and passes it to your next step, such as updating a database or sending a Slack alert. This ensures that your visual data remains within your controlled environment and the Roboflow ecosystem without unnecessary copies.
Ceven focuses on the execution and monitoring of your models rather than the training phase. While the agent can run workflows and validate schemas, it does not directly trigger the training of new model versions inside the Roboflow dashboard. You should train your model and generate a new version in Roboflow first. Once the new version is deployed to the inference server, you can use Ceven to validate the new workflow schema and then switch your production traffic to the updated version. This separation ensures that a human always signs off on model accuracy before the agent begins running inference on live production data.
Ceven uses the Get Server Info and Get Server Metrics tools to proactively monitor the health of your Roboflow deployment. You can build a workflow that checks these metrics every few minutes. If the agent detects that the server is unresponsive or that Prometheus metrics show a critical failure, it can trigger an emergency alert to your engineering team. Because Ceven manages the execution loop, it can also be configured to retry the request after a short delay or route the image to a backup inference server if you have a redundant setup in place to avoid data loss.
Yes, Roboflow applies different rate limits based on your specific plan tier. For example, free and starter tiers have much tighter constraints on the number of concurrent inference requests compared to enterprise plans. If Ceven triggers a massive batch of images simultaneously, you might encounter a 429 Too Many Requests error from the Roboflow API. To handle this, we recommend using a queue system within your Ceven workflow to throttle the requests. This ensures that your agent stays within your plan limits while still processing every image in the queue without dropping frames or crashing the workflow.
Absolutely. One of the best ways to use Ceven with Roboflow is for A B testing. You can set up a workflow that sends the same image to two different Roboflow workflow specifications and compares the results. The agent can use the Describe Workflow Interface tool to ensure both versions accept the same input types and then log the confidence scores from both models into a spreadsheet. This allows you to verify if a new model version actually improves detection accuracy on your real world data before you fully commit to the update in your production environment.
Ceven supports any model that can be wrapped into a Roboflow workflow, including object detection, instance segmentation, and classification. Since the agent interacts with the workflow engine rather than the raw model file, it can handle any combination of blocks you build in the Roboflow interface. Whether you are counting items in a box or identifying a specific part in a machine, as long as the Roboflow workflow returns a standard JSON response, Ceven can parse that data and use it to drive subsequent actions in your business process regardless of the model architecture.
Ceven stores your Roboflow API keys using industry standard encryption at rest. These keys are never exposed in plain text to the model or to other users of your workspace. When the agent makes a call to the Roboflow API, the key is injected into the request header at the system level. You can rotate your keys in the Roboflow dashboard at any time and update them in the Ceven connection settings. We recommend using a dedicated API key for Ceven rather than your primary account key to make auditing and permission management easier for your team.
The current integration is optimized for the inference and deployment side of Roboflow. This means the agent is built to run workflows, check server health, and validate schemas. It is not designed to upload raw images for labeling or manage the annotation process within the Roboflow dataset manager. For those tasks, you should continue using the Roboflow web interface or their dedicated dataset API. Ceven is the layer that takes your finished, trained model and turns it into a functional automated process that interacts with the rest of your software stack.

Alternatives to Roboflow

Other tools that solve a similar problem. Ceven supports these too, so you can switch or run more than one at once.

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