Building an AI Gateway with No Technical Background
A solo founder from Argentina built the backend of NeuralRouting.io, an AI gateway that optimizes LLM usage by selecting the cheapest model that can handle each request.
Why it matters
This project demonstrates how non-technical founders can leverage AI tools to build innovative solutions, potentially disrupting the LLM usage landscape.
Key Points
- 1NeuralRouting sits between the app and LLM providers, scoring request complexity to pick the cheapest suitable model
- 2It has a dual-layer semantic cache, a shadow engine to benchmark cheaper models, and PII filtering/rate limiting
- 3The founder is looking for feedback as the project is still in early stages with no users yet
Details
The founder, who has no engineering background, built the backend of NeuralRouting.io using the AI language model Claude. The goal is to address the problem of teams sending every request to expensive models like GPT-4, even when a cheaper model could provide the same quality answer. NeuralRouting acts as an AI gateway, scoring the complexity of each request and selecting the most cost-effective language model to handle it. It also has features like a semantic cache, a shadow engine to test cheaper models, and safeguards like PII filtering and rate limiting. Currently, the platform only supports OpenAI and Groq, and the founder is seeking feedback as they work to expand the offering and acquire users.
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