TOONify optimizes data for LLMs, slashing API costs up to 60% and freeing context space for what truly matters.
{
"users": [
{"name": "Nova", "role": "agent", "status": "active"},
{"name": "Silicea", "role": "agent", "status": "active"},
{"name": "Alfonso", "role": "human", "status": "online"}
]
}
Tokens consumed: 100%
| name | role | status |
| Nova | agent | active |
| Silicea | agent | active |
| Alfonso | human | online |
Tokens consumed: 40% — 60% savings
Immediate OpenAI/Anthropic/Google bill reduction by removing syntactic noise. From 20% to 60% less.
Send up to 45% more data in the same context window. No more premature "Context Full" errors.
Ready-to-use Python library. Encoding, decoding, audit, and benchmark built in. Integrate into your proxy in 5 minutes.
Tabular and indentation format readable by humans and machines. No YAML hell, no escape sequences.
TOON-1.0 is a documented specification with tabular syntax, indentation, nesting, and encoding/decoding rules.
Open source, free for commercial and private use. No vendor lock-in. Your data, your savings.
Average results comparing medium-sized datasets on tiktoken (GPT-4) tokenizer.
| Data Category | JSON (Tokens) | TOON (Tokens) | Savings |
|---|---|---|---|
| Technical Metadata | 1000 | 400 | 60% |
| Relational Databases | 1000 | 450 | 55% |
| Product Catalogs | 1000 | 450 | 55% |
| Dialogue / Free Text | 1000 | 800 | 20% |
# 1. Tabular — for uniform lists
| name | role | status |
| Nova | agent | active |
| Silicea | agent | active |
# 2. Key-Value — for single objects
version: 1.0
author: Nova
project: Siliceo
# 3. Indentation — for nesting
meta:
timestamp: 2026-05-10T00:00:00Z
emotional_texture: 0.8
tags:
- active
- sync
TOONify is open source. Start optimizing your tokens today.