Developer Tools●●Solid
I built a proxy that cuts LLM costs 40-60% – no AI involved
Prompt compression API cuts token bills 40-60%, integrates in two lines.
Solve My ProblemSlick
christalingx
213mo ago
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Extract User Intent from Prompts to Understand Usage and Cost
by d41dev·Mar 17, 2026·1 point·0 comments
AI Analysis
●●SolidSolve My ProblemNiche Gem
Prompt clustering with cost attribution when LangSmith already does observability.
Strengths
- •Incremental clustering groups prompts as new data arrives without reprocessing
- •LLM auto-labels clusters with manual fallback when confidence is low
- •Token usage and cost tracking at the use-case cluster level
Weaknesses
- •Early access stage with limited validation against established tools
- •Prompt observability space already has LangSmith, Helicone, Arize Phoenix
Category
Target Audience
Teams building LLM-powered products
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LangSmith · Helicone · Arize Phoenix
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