Jet

Most JSON you send to LLMs is wasting tokens. Every repeated key, every unnecessary quote, every verbose structure adds up. And when you're paying per token, that waste becomes expensive fast.

Jet (JSON Efficient Tokenizer) solves this by automatically analyzing your JSON structure and applying the most efficient encoding strategy for each part, cutting token usage by 30-55% without losing any information.

Standard JSON is human-readable, but it's inefficient for LLMs. Every key gets repeated, every bracket and quote costs tokens, and uniform arrays waste massive amounts of space. Jet transforms your JSON into formats that are more compact, easier for LLMs to parse, and significantly cheaper to send.

The tool automatically selects the best approach for each section of your data—whether that's table-like formats for uniform arrays, cleaner YAML-style formatting for objects, or compact notation for simple lists. It's deterministic and lossless, so you can decode it back to the original JSON if needed.

Beyond JSON compression, Jet includes a custom AI model (under 1GB) that converts raw, unstructured text directly into structured JSON. This means you can feed in free-form text and get optimized, token-efficient output in one step—first transforming text to JSON, then compressing that JSON for maximum efficiency.

Token costs add up quickly. Sending 10KB of JSON might cost 2,500 tokens. Jet can cut that by 30-55% depending on structure. For high-volume use, that's meaningful savings. More importantly, the optimized format is often easier for LLMs to understand, potentially improving accuracy on structured data tasks.

The complete Jet system includes a production-ready API, a dedicated server for running the AI model, and a browser-based demo that shows token savings in real-time. It's designed for anyone working with LLMs who wants to reduce costs and improve efficiency without changing their workflow.