You're Paying Too Much for LLMs

Cut token costs and reduce latency — without sacrificing output quality
with just three lines of code
for no cost at all 🎉

(It's actually free)

What is PromptFold?

PromptFold is prompt compression API for LLMs that is real-time, lossless and low latency.
It dynamically reduces input token usage while preserving meaning and intent, and automatically optimizes prompts to reduce unnecessary output token count.

PromptFold is fine-tuned for conversational LLM applications like support bots, task assistants, and interactive AI agents.

Example Compressions

USER INPUT
"can you hlp me file a claim?"
9 tokens
PromptFold
44ms
COMPRESSED
"help file claim"
3 tokens
(66.67% reduction)
CHAT BOT RUNNING:
OpenAI
Anthropic
Google
etc.
USER INPUT
"Hi. I would like to look for a Mexican restaurant, please. I need a table for 4 at 10pm. thank you"
28 tokens
PromptFold
36ms
COMPRESSED
"Want to find Mexican restaurant. Need table for 4 at 10pm. Thanks"
17 tokens
(39.29% reduction)
CHAT BOT RUNNING:
OpenAI
Anthropic
Google
etc.
USER INPUT
"Hllo, i need your asistnce with chaging mypassword"
15 tokens
PromptFold
24ms
COMPRESSED
"Help with changing password"
4 tokens
(73.33% reduction)
CHAT BOT RUNNING:
OpenAI
Anthropic
Google
etc.

Fast

Sub-50ms response times

Lossless Compression

20–50% prompt compression with perfect semantic fidelity

Massive Savings

Save thousands per month on OpenAI, Anthropic, and other API costs

Universal compatibility

Works with OpenAI, Anthropic, Google, Cohere, and any other AI model provider

Scalable

Optimized infrastructure supports all system needs from individual builders to enteprise companies

Easy Integration

Only three lines of code required

Performance on Real Data

Evaluated on thousands of real dialogues from industry-standard datasets—actual customer service and task-oriented conversations, tested end-to-end via our production API.

MultiWOZ Dataset

MultiWOZ is a 10k-dialogue, multi-domain task-oriented dataset collected by University of Cambridge researchers, covering domains like hotels, restaurants, taxis, and trains.

📈 Compression Results on 2,000 Dialogues:

30.3%
Average Token Reduction
56ms
Average Response Time
(P99: 84ms)
99%
Rate of Lossless Compression
29.6K → 20.6K
Total Token Reduction

Taskmaster-2 Dataset

Real support chat dialogues from Google's Taskmaster dataset—actual customer service conversations covering claims, bookings, inquiries, and technical support.

📊 Compression Results on 2,000 Support Dialogues:

30%
Average Token Reduction
63ms
Average Response Time
(P99: 111ms)
99%
Rate of Lossless Compression
25.8K → 18K
Total Token Reduction

Estimated Cost Savings

Real savings calculations based on our Google Taskmaster evaluation showing 30% input token reduction across 2,000 support dialogues.

$500/mo
Current API spend
Save $150/mo
with 30% reduction
$2K/mo
Current API spend
Save $600/mo
with 30% reduction
$10K/mo
Current API spend
Save $3K/mo
with 30% reduction
$500K/mo
Current API spend
Save $150K/mo
with 30% reduction

* Savings based on 30% token reduction from Google Taskmaster evaluation. Results verified on 2,000 real support dialogues.

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