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Getting Started with ScaleDown: Your AI Cost Optimization Guide

ScaleDown Team • March 13, 2025 • 10 min read ScaleDown is a context engineering platform that intelligently compresses AI prompts while preserving semantic integrity and reducing hallucinations. Our research-backed compression algorithms analyze prompt components—from reasoning chains to code contexts—and apply targeted optimization techniques that maintain output quality while dramatically reducing token consumption. banner

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Our Technology Stack:

  1. Reasoning Module Optimization: Dynamic model merging based on query difficulty
  2. Code Context Compression: AST-based semantic filtering for programming tasks
  3. Multimodal Audio Processing: Semantic tokenization for audio-visual applications
  4. Benchmark-Driven Validation: Rigorous quality preservation across evaluation frameworks

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What is ScaleDown?

ScaleDown is an intelligent prompt compression service that reduces your AI token usage while preserving the semantic meaning of your prompts. Think of it as a smart compression tool for your AI conversations. You get the same quality responses while paying significantly less.

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Before You Start

To use ScaleDown, you’ll need:
  • An API key
  • Basic knowledge of making API calls
  • Your existing AI prompts that you want to optimize
Ready to get your API key? Contact our sales team.

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Your First ScaleDown Request

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Step 1: Set Up Your Request

Here’s how to make your first API call to compress a prompt.
  • Python
  • TypeScript
  • JavaScript
import requests
import json

# ScaleDown API endpoint
url = "[https://api.scaledown.xyz/compress/raw/](https://api.scaledown.xyz/compress/raw/)"

# Your headers (replace YOUR_API_KEY with your actual key)
headers = {
    'x-api-key': 'YOUR_API_KEY',
    'Content-Type': 'application/json'
}

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Step 2: Configure Your Compression

Separate your context from your main prompt and set the compression rate to "auto" for the best results.
  • Python
  • TypeScript
  • JavaScript
payload = {
    "context": "Context about your specific topic or instructions here",
    "prompt": "Your actual query or question here",
    "model": "gpt-4o",
    "scaledown": {
        "rate": "auto" # Automatic compression rate optimization
    }
}

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Step 3: Make the Request

With your request set up and configured, you can now execute the API call.
  • Python
  • TypeScript
  • JavaScript
response = requests.post(url, headers=headers, data=json.dumps(payload))
result = response.json()

print(result)
That’s it! Your prompt is now compressed and ready to be used with your AI model.

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Understanding the Response Structure

The API response provides the compressed prompt along with useful metadata about the operation. 
{
  "compressed_prompt": "Your optimized context here...",
  "model_used": "gpt-4o",
  "original_prompt_tokens": 150,
  "compressed_prompt_tokens": 65,
  "successful": true,
  "latency_ms": 2341,
  "request_metadata": {
    "compression_time_ms": 2341,
    "compression_rate": "auto",
    "prompt_length": 425,
    "compressed_prompt_length": 189
  }
}

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Supported Models

The model parameter in your request payload specifies the target AI model. Here are the currently supported models: Gemini
  • gemini-2.5-flash
  • gemini-2.5-pro
  • gemini-2.5-flash-lite
  • gemini-2.0-flash
OpenAI
  • gpt-4o
  • gpt-4o-mini