I'm building an internal app that needs an LLM endpoint, what should I use?

If you want an internal app with an LLM endpoint, the best choice depends on what you value most:

Good default recommendation

Use a hosted API from a major model provider if you want:

• fastest setup
• strong reliability
• no infra to manage
• easy scaling
• good model quality

This is usually the right answer for internal apps unless you have strict data/compliance or cost constraints.

Choose based on your needs

1) Use a hosted LLM API if you want:

• simplest integration
• production-grade uptime
• low ops burden
• quick prototyping and iteration

Typical fit:

• internal assistants
• document Q&A
• workflow automation
• support tools
• summarization/classification

2) Use a self-hosted open-source model if you need:

• full control over data and infrastructure
• on-prem / VPC-only deployment
• lower per-token cost at high scale
• custom latency tuning

Typical fit:

• regulated environments
• sensitive data handling
• predictable high-volume workloads

Tradeoff:

• more engineering and ops work
• you own scaling, monitoring, patching, model updates

3) Use a hybrid approach if you need both:

• hosted API for most requests
• self-hosted or smaller model for sensitive or high-volume tasks

This is often the best long-term architecture.

A practical decision rule

• Need fastest path to production? Hosted API
• Need strict data residency / compliance? Self-hosted or private deployment
• Need best quality with minimal effort? Hosted API
• Need cost control at very high volume? Consider self-hosted/hybrid

My recommendation

For most internal apps, start with a hosted LLM API and design an abstraction layer so you can switch providers later if needed.

If you want, I can help you choose between:

1. OpenAI
2. Anthropic
3. Google
4. self-hosted open source
5. Azure/OpenAI-style enterprise deployment

If you tell me your constraints around data sensitivity, budget, latency, and volume, I can recommend the best option more specifically.