Do I need a model serving platform for a small internal app?

Usually no — not for a small internal app.

A model serving platform is most useful when you need things like:

• High availability / uptime
• Autoscaling under unpredictable traffic
• Low-latency inference at moderate to high request volume
• Versioning / A-B testing / rollbacks
• Monitoring, logging, and observability
• Multiple models or frequent model updates
• Governance / security / access control across teams

For a small internal app, a simpler setup is often better:

• A single API service that calls the model directly
• A scheduled/batch job if real-time responses aren’t needed
• A lightweight deployment on something like:
  • a VM
  • Docker on a small server
  • a serverless function
  • a simple FastAPI/Flask app

A good rule of thumb

You probably don’t need a model serving platform if:

• usage is low or predictable
• only a few internal users access it
• downtime isn’t a big issue
• you have one model or a very small number of models
• you can tolerate manual deployments

You probably do need one if:

• the app becomes business-critical
• request volume grows
• you need strict latency targets
• you have many models or frequent releases
• you want proper MLOps workflows

Practical recommendation

For most small internal apps:

1. Start with a simple API service
2. Add basic logging + monitoring
3. Revisit a serving platform only when pain appears

If you want, I can help you decide based on your specifics — e.g. number of users, expected traffic, model type, and whether it needs real-time responses.