Machine Learning Platform Support Request

Managing a machine learning platform requires fast, efficient support for complex technical issues. Our Machine Learning Platform Support Request template helps data science and ML engineering teams capture detailed diagnostic information, prioritize incidents, and route issues to the right specialists—all without interrupting critical model development and deployment workflows.

Built for IT teams, SaaS companies, fintech platforms, and any organization running production ML infrastructure, this template replaces scattered Slack messages and email chains with a structured support pipeline that captures everything your ML engineers need to troubleshoot effectively.

Why ML platform support needs a specialized form

Machine learning infrastructure issues are different from standard IT tickets. A model training failure might involve framework versions, hardware configurations, dataset lineage, hyperparameter conflicts or infrastructure limits. A deployment issue could stem from API incompatibilities, serving infrastructure, model registry problems or container orchestration failures. Generic support forms miss the context engineers need, leading to endless back-and-forth before resolution even begins.

This template asks the right questions upfront—model frameworks, error logs, affected environments, reproduction steps and business impact—so your ML engineering team can diagnose and resolve issues faster. Conditional logic adapts the form based on issue type, and automatic escalation rules ensure critical production failures reach senior engineers immediately.

What's included

The form captures reporter contact details, urgency level, affected platform component (training, deployment, feature store, infrastructure), detailed issue descriptions, environment specifics, error messages, and any relevant logs or screenshots. Based on severity and category, the form can automatically route to different support tiers or trigger alerts via Stepper for production-critical incidents.

Paperform's calculation engine can even implement smart priority scoring based on combinations of urgency, affected users, and environment type—helping your team triage effectively when multiple issues arrive simultaneously.

Integrate with your existing ML stack

Connect this form directly to your incident management tools via Stepper, Zapier or webhooks. Send high-priority tickets straight to PagerDuty, log all requests in Jira or Linear, notify on-call engineers via Slack, or update your internal knowledge base in Notion or Confluence. All without writing a single line of code.

For teams managing ML platforms across multiple clients or business units, Paperform's Agency+ plan lets you deploy branded versions of this template for each stakeholder group while maintaining central oversight of all support operations.

Whether you're running TensorFlow, PyTorch, MLflow, Kubeflow or a custom ML platform, this template gives your support workflow the structure and speed it needs to keep data scientists productive and models shipping on schedule.