ceven

Vectorshift

Triggers AI pipelines, manages knowledge bases, and deploys chatbots to automate complex data processing and customer interaction flows.

Try Vectorshift in Ceven

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Why use Ceven?

  1. AI native Vectorshift integration

    • Describe the outcome and Ceven picks the right Vectorshift 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 Vectorshift data, across all 11 of its actions.

  2. Managed auth

    • Built in OAuth with automatic token refresh and rotation.
    • One place to manage, scope, and revoke Vectorshift 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 Vectorshift, when, and on whose behalf.
    • The agent pauses and asks when Vectorshift is unclear instead of plowing ahead.

  4. Enterprise grade security

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

Supported tools

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

Create Chatbot
Use this when you need to deploy a new conversational interface tied to a specific pipeline configuration.
Delete Chatbot
Permanently remove a chatbot by its ID when it is no longer needed for a project.
Get Chatbot
Pull the configuration and metadata for a specific chatbot using its ID or name.
Get Knowledge Base
Retrieve the settings and metadata for an existing knowledge base by ID or name.
Get Pipeline
Pull the full configuration and metadata for a specific pipeline to verify its logic.
List Chatbots
Pull a list of all available chatbots in the account to find specific IDs.
List Knowledge Bases
Retrieve all knowledge bases in the account to identify the correct data source.
List Pipelines
Pull the full catalog of pipelines, optionally filtering for shared assets.
List Transformations
Retrieve all available data transformations to understand how inputs are being modified.
Run Pipeline
Execute a pipeline with specific inputs to get an immediate result or a run ID.
Run Pipeline in Bulk
Process multiple sets of inputs through a pipeline in a single batch call.
Terminate Pipeline Execution
Stop a running pipeline execution immediately using its unique run ID.

12 actions · scroll to see them all

Frequently asked questions

Ceven manages long running pipelines by capturing the run ID returned by the initial request. Instead of keeping a connection open and risking a timeout, the agent periodically polls the status of the execution. Once the pipeline reaches a completed or failed state, the agent retrieves the final output and continues the workflow. If a pipeline is taking longer than your specified threshold, you can use the terminate action to kill the process and prevent wasted credits. This ensures that your business processes do not hang while waiting for complex AI reasoning tasks to finish in the VectorShift cloud.
Yes. You can build a Ceven workflow that monitors a folder in Google Drive or a Slack channel and then triggers the appropriate VectorShift actions to update your knowledge base. While the current API focus is on retrieval and listing, you can use the pipeline run action to send new data into a pipeline that is specifically designed to upsert information into a knowledge base. This creates a self updating loop where your AI chatbots always have access to the most recent company documentation without any manual upload process from your team.
VectorShift enforces rate limits based on your specific subscription tier which can lead to 429 errors during massive bulk uploads. Ceven handles this by implementing an exponential backoff strategy. If the agent receives a rate limit notification, it will pause and retry the request after a short delay. However, for extremely large datasets, we recommend splitting your bulk requests into smaller batches of fifty records. This prevents the VectorShift API from flagging the traffic as abusive and ensures that your data processing completes without manual intervention or workflow failure.
Ceven can create chatbots and manage existing pipelines, but it cannot visually design the internal nodes of a VectorShift pipeline. The pipeline logic must be built using the VectorShift drag and drop editor first. Once the pipeline is published and has a valid ID, Ceven can trigger it, pass variables into it, and use the output in other SaaS tools. Think of VectorShift as the place where you design the AI logic and Ceven as the operator that decides when to run that logic and where to send the resulting data.
Ceven uses secure API key management to communicate with VectorShift. Your keys are encrypted at rest and are never exposed to the end user or the model during the execution of a prompt. We follow the principle of least privilege, meaning the agent only accesses the specific pipelines and knowledge bases required to complete the task you requested. All calls are made over HTTPS, ensuring that the data moving between your knowledge base and your other SaaS tools remains private and protected from interception during transit.
Absolutely. One of the primary strengths of using Ceven with VectorShift is the ability to chain pipelines together. For example, you can run a classification pipeline first to determine the intent of a customer email. Based on that output, the agent can then choose to run a specific extraction pipeline or a summarization pipeline. The output of the first VectorShift run becomes the input for the second, allowing you to build highly sophisticated AI logic that would be too complex to manage within a single pipeline file.
When running pipelines in bulk, VectorShift returns an array of statuses for each individual input. Ceven parses this array to identify exactly which rows failed and why. Instead of failing the entire workflow, the agent can be configured to log the errors to a spreadsheet and only proceed with the successful results. You can then review the failures, fix the source data, and tell the agent to retry only the failed records, which saves time and prevents duplicate processing of the entries that were successful.

Alternatives to Vectorshift

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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Plug Ceven on top of the tools you already run. Connect Vectorshift and the rest of your stack, describe the outcome, and its agents handle the work end to end, days of it in minutes.

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