Developer Tools1 month ago
SuperCompress - Cut Your LLM Token Costs by 65%
Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X
The full gallery
Tech stack
19 projects
Compress prompts before LLM API calls to reduce token usage and costs.
@asgujjuasitgets · X
Automatically route each prompt to the cheapest capable model to cut API costs.
u/ASDKING100 · Reddit
Launched an AI API router tonight, and found a bug hours in that would've taken real payments without ever upgrading the account Built LLMLite over the past few weeks — it classifies each prompt and routes it to the cheapest model that can actually handle it, instead of hitting GPT-4o for everything. Free tier, no card needed to try it. Tonight, right as I was about to launch, ran a real transaction to test the payment flow end to end. Paddle processed it, webhook fired, signature verified
Convert PDF, DOCX, XLSX, CSV, JSON, XML, HTML, Images to clean Markdown optimized for AI Agents, RAG, and Vector DBs. 100% Privacy-First, In-Browser Conversion.
@13SahajChawla · X
For professionals to redact their client's sensitive informations before giving AI to process it & while converting any kind of document to a structured MD file. Better quality outputs, 100% privacy with on-browser local processing, and fully free!
Practice LeetCode problems with automated spaced repetition scheduling.
@JoydeepNath007 · X
Analytics dashboard for LLM API spending by model and environment with optimization suggestions.
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to
Semantic caching reduces LLM token costs and latency for AI queries.
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]
Send your question to a panel of LLMs that peer-review each other and return one synthesized answer.
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree
Tests LLM endpoints with adversarial cases and provides OWASP-mapped security audit reports.
@aryaan_sheth · X
- LLM security for small teams
Route your LLM API requests across multiple providers to cut costs and meet latency targets.
Aperswal · HN
Made a Free LLM Router
Generate videos, images, music, code, and 3D objects using frontier AI models.
laurentiurad · HN
I built and run several SaaS platforms: - https://dave-bot.com -> a full-stack AI platform where you can generate videos, images, music, code, 3d objects with frontier Gen AI models. - https://headsnap.io -> a platform that you can generate images of yourself based on 4 selfies. - https://quantiq.live -> a service providing financial and historical data for stocks, as well as government trades. - https://aivestor.tech -> an AI agent that picks small/midcap stocks and trades them using Alpaca API
View LLM model rankings across 10 benchmark questions.
fristovic · HN
She watched me look at model rankings and asked what do the numbers mean... I literally had no good way of explaining it to her so I just came up with something that is approximately in the same ballpark as some of the benchmarks out there lol