实用工具1 week ago
Velum | Mask sensitive data before it reaches any AI
向任何LLM发送前屏蔽敏感数据，然后在回复中恢复。
@velumprivacy · X
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向任何LLM发送前屏蔽敏感数据，然后在回复中恢复。
@velumprivacy · X
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
分享链接上传收据，LLM 自动分类和整理。
jahnoikka · HN
Sorted Receipts - clients dump receipts in one link, LLM sorts them
对比多个LLM API提供商的延迟和吞吐量性能。
@QAInsights · X
Calla AI语音前台，接听漏接电话，预订工作，追踪收入。
@Jithendhar40266 · X
Ai voice agents that books calls
监控AI应用中的模型调用、代理步骤和检索，追踪令牌、成本和延迟。
ephraimduncan · HN
Observability for Coding Agents and LLM Applications
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
An LLM gateway for OpenAI, Anthropic, Google and Azure. Every request logged, priced to the token, and audited for waste you can actually recover.
@razdagan3 · X
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
在安全的团队工作区中比较和使用多个LLM模型（Claude、OpenAI、Gemini等），用您自己的API密钥。
@uncoolavatar · X
检测LLM API是否被降智或偷换模型，一键跑6项探针得出结果
cocodot LLM 降智检测 — 免费的 LLM API「降智/偷换模型」在线检测：填入任意 OpenAI 兼容端点的 base_url 和临时 API Key，跑 6 项探针（模型声明、动态题、能力完整性等）生成分项报告；Key 仅用于当次检测、不落库不留存，检测方法[开源](https://github.com/cocodot2026/cocodot-llmprobe)