SuperCompress fitHigh fit
—/100
Your product shows the patterns where context compression tends to pay back fastest.
SuperCompress AI Score
See your compression fit.
Enter your website. We’ll analyze the public site and build a specific readout for your product.
Analyzing your public site
Context.dev is reading the pages that matter.
Private assessmentContext.dev analysisAuth only for the final readout
Analysis in progress
One number while we
One number while we
read your context.
What do you spend each month on LLM input tokens? We’ll use it to make your savings estimate specific.
Context.dev is scraping your public pages in the background.Your first readout
Your context has room to breathe.
Estimated monthly savingsYour input
$—at your spend
Based on your slider and the assessment’s estimated compression opportunity.
SC
The useful part is ready
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why behind it.
Sign in to see the signals we found and your personalized SuperCompress implementation plan.
We use your account only to save access to this assessment.Why this score
Your stack likely creates repeated, oversized context.
Your implementation path
Where SuperCompress fits in your stack.
Generated from your Context.dev assessment.
Loading your specific plan…
The practical next step
Put compression in front of your model call.
Keep the evidence. Drop the noise. Pay for fewer input tokens on every request.
This is a directional estimate, not a quote. Your actual savings depend on model, traffic, context size, and current input pricing.