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Building AI-Native Applications

How to leverage OpenAI and credit systems to build the next generation of intelligent software.

Jane Doe

Jane Doe

Building AI-Native Applications

Artificial Intelligence is no longer just a buzzword - it's a requirement for modern software. But integrating LLMs (Large Language Models) isn't just about making an API call to OpenAI. It requires a rethink of your application's architecture.

The Cost of Intelligence

AI is expensive. Every token generated costs money. If you offer unlimited AI access to your users, your infrastructure bills will skyrocket.

This is why we built a robust Credit System into Achromatic.

Usage-Based AI

The best way to monetize AI features is to tie them to consumption.

  1. Grant Credits: Give users a monthly allowance based on their subscription tier.
  2. consume Credits: Deduct credits for every AI interaction (e.g., 1 credit per message or variable based on token count).
  3. Top-ups: Allow users to purchase additional credit packs when they run low.

The User Experience

Achromatic includes a production-ready Chat UI that handles:

  • Streaming Responses: For that snappy, real-time feel.
  • History & Context: Storing conversation threads.
  • Optimistic Updates: Making the UI feel instant.

Building AI apps requires more than just prompts. It requires infrastructure for billing, rate limiting and state management. Achromatic provides this foundation out of the box, so you can focus on fine-tuning your models.