LLM token optimization for apps, agents and RAG

Spend less on every LLM call.

Compress prompts, files, logs, system instructions, and RAG context before they hit GPT, Claude, Gemini, or any model provider. Preserve critical terms, reduce waste, and estimate cost savings instantly.

42%

Average reduction

80%+

RAG savings

Any LLM

Provider support

compression engine

Original

1,248

tokens

Optimized

612

tokens

Saved

50.9%

reduction

Before

Bloated

Please make sure to return the full code. Please make sure to return the full code. The API response must include response_code, message, data, and meta. Do not remove existing validation.

After

Caveman

- return full code

- API response include response_code, message, data, meta

- keep current validation

Risk score

Low

Est. monthly savings

$318.40

Built for teams using long prompts, agent memory, files, logs, and RAG.

GPTClaudeGeminiMistralLlamaCustom LLM

Product

Not a prompt enhancer. A compression layer before inference.

Prompt enhancers make inputs longer. TokenSave removes waste while preserving entities, requirements, output format, and task intent.

Prompt compression

Compress long prompts, system instructions, logs, files, and agent context without losing important meaning.

Protected terms

Keep API routes, JSON keys, variable names, amounts, dates, schema fields, and business rules untouched.

Provider-aware savings

Compare estimated savings across GPT, Claude, Gemini, Mistral, Llama, and other model providers.

Where savings come from

Small prompts save some. Context-heavy workflows save a lot.

System prompts

Remove repeated rules and verbose wording while preserving non-negotiable instructions.

46%

Before

2,800

tokens

After

1,520

tokens

RAG context

Reduce retrieved context before sending it into expensive long-context model calls.

87%

Before

48,000

tokens

After

6,400

tokens

Agent loops

Compress repeated tool traces, memory blocks, logs, and task history across multi-step agents.

58%

Before

12,400

tokens

After

5,180

tokens

Compression modes

Choose safety, balance, or maximum savings.

Safe mode protects production prompts. Caveman mode aggressively converts verbose instructions into short, direct commands.

10–25%

Safe

Low-risk cleanup for production prompts.

20–45%

Balanced

Best default for prompt and context optimization.

45–75%

Caveman

Maximum compression. Short, direct, command-style output.

API ready

Add compression before your existing model call.

Use it as a pre-processing layer before OpenAI, Anthropic, Google, local models, or your own agent execution pipeline.

Protect JSON keys

Compress file context

Reduce agent traces

Validate meaning

compression api

Compression API

Ready
POST /v1/compress

{
  "mode": "balanced",
  "provider": "openai",
  "preserve": [
    "response_code",
    "student_uuid",
    "payment_id"
  ],
  "input": "Long prompt or file context..."
}

Pricing

One simple price. Less than one coffee.

Compress prompts, files, logs, RAG context, and OpenClaw agent context before expensive model calls.

Early builder price

Token Saver

$4.99

/month

One simple plan for builders who want to reduce token waste before every LLM call.

Prompt analyzer

Safe, balanced, aggressive, and caveman modes

File, log, RAG, and agent context compression

Protected JSON keys, IDs, URLs, and code terms

GPT / Claude / Gemini / generic token estimate

OpenClaw context compression

Cancel anytime

Cut token waste before every LLM call.

Start with prompt compression. Expand into file compression, agent context pruning, and provider-aware token cost optimization.