Monitor a hosted web form, convert uploads to data URIs, call easybits Extractor for classification, and route or log results automatically.
This AI Agent automates the intake of documents via a web form, converts each upload to a properly formatted data URI, and calls the easybits Extractor API to assign a single category. It returns a precise document_class label (e.g., medical_invoice, restaurant_invoice) for consistent routing. The agent can trigger downstream actions like saving to storage, notifying teams, or logging results for audits.
A concise description of the agent’s function in practice.
Accepts file uploads from a hosted web form.
Converts binary uploads to base64 and builds a data URI with the correct MIME type.
Posts the data URI to the easybits Extractor API for classification.
Returns the document_class label and stores it for routing decisions.
Routes the document to your chosen destination or logs the result.
Alerts or logs unrecognized or null classifications for review.
Two sentences of explanation.
A simple 3-step flow that anyone can follow.
A user uploads a file through the hosted web form, triggering the agent workflow.
The binary file is decoded, converted to base64, and a proper data URI is created with the correct MIME type.
The data URI is POSTed to the easybits Extractor API, which returns a single document_class label for routing or logging.
A realistic, concrete scenario with time and outcome.
A procurement administrator uploads an invoice (PDF) via the hosted web form. The AI Agent converts the file to a data URI, sends it to easybits Extractor, and receives a document_class of restaurant_invoice. The system then routes the file to the “Restaurant Invoices” folder and logs the result with the timestamp for auditing, all within seconds.
Roles that gain value from automated document classification.
Needs fast, reliable invoice categorization to accelerate AP workflows.
Wants consistent taxonomy and automated routing for supplier documents.
Requires auditable classification history and clear provenance.
Seeks low-code integration with existing systems.
Needs categorization to simplify supplier document management.
Must classify onboarding and policy documents accurately.
Key tools that work with this AI agent and what it does inside each.
Performs the category classification via API and returns document_class.
Orchestrates the form upload, data URI construction, and API call sequence.
Moves or copies the document to a folder named after its category.
Sends alerts when a document cannot be classified or is uncertain.
Appends a row with document name, category, timestamp, and source.
Practical scenarios where this AI agent shines.
Common questions and detailed answers about using this AI agent.
The web form accepts PDFs, PNGs, and JPEGs. The agent reads the MIME type from the upload to construct a proper data URI and sends that to easybits Extractor for classification. Large files may require chunked handling or batching, but typical invoices and documents classify in a single call. If you need support for additional formats, you can update the workflow pipeline configuration in easybits and your n8n setup. All data is transmitted securely over HTTPS during the API call.
A null or uncertain classification triggers a review path. You can route such documents to a fallback folder, notify a reviewer, or log the item for manual labeling. This ensures nothing is lost and provides an auditable trail for later refinement of categories. You can also adjust the classifier prompt to reduce uncertainty by expanding or refining categories. The workflow can be configured to escalate automatically when confidence is below a threshold.
Yes. Categories are defined in the easybits Extractor pipeline as the target labels. You can add, rename, or remove categories and update the classification prompt to reflect your taxonomy. After updating, re-test with representative documents to confirm consistent labeling. The agent will use the updated categories in subsequent classifications without code changes to the orchestration. This keeps taxonomy aligned with business needs.
No. The solution is designed as a low-code workflow. You configure the easybits Extractor pipeline and connect it via the HTTP node in n8n. The AI agent handles the data URI creation and API call automatically. If you can configure a form URL and an API key, you can deploy this in minutes and adapt as your needs evolve.
Data is transmitted over HTTPS during the API call to easybits Extractor. Access to the pipeline is controlled via Bearer authentication. You should apply your organization’s standard security practices, including limiting access, logging usage, and ensuring storage destinations comply with data governance requirements. If sensitive documents require additional protection, consider encrypting data at rest and implementing stricter access controls in downstream systems.
Create and configure your easybits pipeline with the document_class field, then connect the n8n workflow to the pipeline API. Activate the workflow, open the hosted form, and upload a test document. Verify that the response includes the correct document_class and that routing and logging occur as expected. Adjust prompts or category mappings as needed and re-test until results are stable. Once satisfied, monitor initial runs to ensure accuracy and reliability.
Yes. The agent is designed to integrate with common storage and workflow systems. You can route categorized documents to folders, cloud storage, or ERP modules, and log classifications in your existing spreadsheets or databases. If you need deeper integration, update the n8n flow to create or update records in your systems automatically based on the classification. This keeps your current tools in play while adding automated labeling.
Monitor a hosted web form, convert uploads to data URIs, call easybits Extractor for classification, and route or log results automatically.
