u/zishansami102

The primary goal is to reduce the LLM API costs on the forntier models keping peroformance the same.

Example cases:

1. Files/Docs to Flowchart generation (10000 files/day)
2. Generic web content to structured output (20000 pages/day)
3. Image generation for blog articles in a particular style (1000 images per day)

The output is challenging enough for us to always use frontier models for the best performance but want to reduce the cost it will incur.

We're approaching this with finetuning open sourced models using traning data from frontier models.

We want to know if others are also facing the heat from the API costs, we would like to chat and build an easy solution to handle this at scale for everyone.

Like document analysis and formatting using LLMs at scale (like 10000 docs/day)

or Content Categorization, small workflow agents, content parsing, image generation etc?

Running these at scale of 10k per day incurs huge costs with frontier models, and small models or opensourced ones are not that peroformant.

Anyonce facing similar porblems and know a workaorund?

Like document analysis and formatting using LLMs at scale (like 10000 docs/day)

or Content Categorization, small workflow agents, content parsing, image generation etc?

Running these at scale of 10k per day incurs huge costs with frontier models, and small models or opensourced ones are not that peroformant.

Anyonce facing similar porblems and know a workaorund?

Like document analysis and formatting using LLMs at scale (like 10000 docs/day)

or Content Categorization, small workflow agents, content parsing, image generation etc?

Running these at scale of 10k per day incurs huge costs with frontier models, and small models or opensourced ones are not that peroformant.

Anyonce facing similar porblems and know a workaorund?