Automate Document Intake for AI and Machine Learning Pipelines with Boilerplate

Building a machine learning or AI pipeline is hard enough—don’t let the file collection step slow you down. Whether you’re fine-tuning an LLM, parsing PDFs with OCR, or embedding unstructured documents into a vector database, the data still needs to come from somewhere.

‍Boilerplate is a prebuilt document intake portal that helps AI teams collect files, e-signatures, and form data from end users, then feed it into your pipeline via JSON-based REST API. It saves you from building a front-end upload experience from scratch, and gives you structured, trackable data ready for preprocessing.

Tame the Chaos of External Document Collection

Machine learning systems are only as good as the inputs they receive. But when the source of your training or processing data is a human—like a customer, client, or third-party partner—collection becomes unpredictable.

Boilerplate solves this by providing a clean, secure, and trackable interface for external users to submit documents, complete forms, and provide digital signatures. Each portal includes:

A list of required files or inputs
Upload status tracking
Automated reminders for incomplete submissions
Real-time updates to your back end

This ensures your models receive complete, clean, and correctly formatted data—no more chasing down email attachments or half-complete uploads.

Built for AI Data Workflows: REST + JSON

Boilerplate uses a RESTful API with JSON payloads to integrate cleanly into your existing data pipeline. You can configure file requirements, monitor upload status, and receive each submission as soon as it’s ready.

Whether you’re feeding files into:

LLM preprocessing tools (LangChain, Haystack, semantic search)
OCR engines (Tesseract, Amazon Textract)
Cloud functions and queues (AWS Lambda, Google Cloud Functions)
Custom embedding and vector store pipelines

Boilerplate helps automate the messy front-end step—so you can stay focused on data engineering and model development.

A Real Use Case: Streamlining Input for Document-Based LLMs

Let’s say you’re building a platform that helps legal teams search and summarize uploaded documents using an LLM. You want your model to perform well—but you're stuck waiting for clients to submit the right files, or worse, emailing back and forth to clarify what’s missing.

Boilerplate fixes this:

You define the intake checklist (e.g., “Lease agreement,” “ID verification,” “Signed waiver”)
Clients see what’s required, upload via secure portal, and digitally sign where needed
You get complete data delivered as structured JSON with file links, ready to ingest

No more inconsistent inputs. No more confusion. Just ready-to-process data for your model.

Plug and Play for AI and ML Teams

Whether you're a solo developer building an intelligent assistant or part of a data science team maintaining a robust AI pipeline, Boilerplate saves you time on:

Front-end upload forms
E-signature logic
Missing file tracking
Input validation

It’s the front end for your back-end AI system.

Start Smarter: Add Boilerplate to Your AI Stack

Don’t burn sprint cycles building file upload logic. Focus on your model—we’ll get you the data.

Try Boilerplate today and see how easy it is to collect the documents, files, and signatures your AI tools need—all through a customizable, developer-ready portal.

Schedule A Free Consultation