Conversational Token System

CTS by Yudi AI

An infrastructural top-layer that natively compresses contextual history, reducing LLM API token costs by up to 80%.

The Cost of Infinite Context

Every time you send a multi-turn conversation to a commercial API (like GPT-4 or Claude), you pay to re-process the entire history. This creates an exponential cost curve that makes persistent AI agents financially unviable for enterprise scaling.

CTS sits as middleware between your application and the model API. Utilizing early paradigms from Yudi AI's CMP architecture, it dynamically compresses conversational state into dense semantic representations, passing only the exact context required for the current interaction.

The 80% Reduction

By preventing the need to pass thousands of raw history tokens per inference request, CTS flattens your cost curve.

Without CTS (100 Turns)
142,500
Cumulative Tokens Billed

Quadratic scaling. Reprocessing history every turn.

With CTS (100 Turns)
28,500
Cumulative Tokens Billed

Linear scaling. Only sending delta context and compressed state.

Integration

CTS is designed to be a drop-in replacement for standard OpenAI/Anthropic SDKs. It natively supports:

Drop-in Replacement

import { CTSClient } from '@yudi/cts'; // Standard initialization, but routed through CTS const client = new CTSClient({ provider: 'openai', apiKey: process.env.OPENAI_API_KEY, ctsKey: process.env.CTS_KEY }); // History is automatically managed and compressed server-side const response = await client.chat.completions.create({ model: 'gpt-4-turbo', sessionId: 'user_123', messages: [{ role: 'user', content: 'What did we discuss yesterday?' }] });
Join the API Waitlist