
SuperCompress - Cut Your LLM Token Costs by 65%
压缩提示词以减少向LLM API发送的token数量和成本。
@asgujjuasitgets · X
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压缩提示词以减少向LLM API发送的token数量和成本。
@asgujjuasitgets · X

FlexInference: 通过多个提供商路由LLM API请求,降低成本和延迟。
Aperswal · HN
Made a Free LLM Router

Ornymo通过语义缓存减少LLM查询成本和延迟。
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]

自动将提示词路由到最便宜的模型,节省API成本。
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

Master system design interviews with a real-time AI interviewer. Draw cloud architectures (AWS, Azure, GCP), explain trade-offs over voice, and get instant scored feedback using th
@Brahimuss2885 · X

对比多个LLM API提供商的延迟和吞吐量性能。
@QAInsights · X

使用一个 API 访问和切换多个 LLM 提供商,同时优化推理成本。
justin2025 · Product Hunt
Auriko Trading desk for LLM calls

追踪您的应用中使用的 AI 模型,并在其被弃用前获得警告。
taylorgt · HN
Find every AI model your code calls and warn before it's retired

向多个前沿大模型提问,获得经过同行评审的综合答案。
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

用对抗测试检查LLM端点安全,获取OWASP审计报告。
@aryaan_sheth · X
- LLM security for small teams

在仪表板上版本管理、测试和部署 LLM 提示词,无需修改代码。
@why_deepanshux · X
I Just launched my first SaaS. Late night coding session, white board and my my markers knows what we built. Now it's world's turn. Please checkout Link below.

Boilerroom 整合销售勘探、拨号、通话录音和自动跟进。
sadidrahimi · HN
hello HN, let me tell you why i built boilerroom ( https://boilerroom.ai ). throughout my past endeavours in sales, the one thing that thoroughly pissed me off was living in a million places to execute one thing; the outbound motion this includes everything top of funnel like finding leads (be it inbound or outbound), researching, filtering for qualification criteria, throwing them in a sequence, engaging them via dialer, email, and linkedin, gathering context, all the way through bottom of funnel like discovery calls, demo calls, and post-sales activities what absolutely does not exist (or if it does, a piss-poor model) is a place to simply execute this work in one place why tf do i have to be on clay, or apollo, clicking around looking for leads, researching them around myself, put them in to some other garbage software to sequence to tell me when to make a call or send out automated emails, only to get a massive backlog of things I was supposed to do, which in turn makes my whol