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60 projects


Monitor, govern, and optimize your AI agents at scale.
@AiShivam · X
AgentStacKPro is an OS for AI agents designed to make them production-ready, and it holds incredible potential. You can also check out the project I currently developed

ARGUS:为AI代理流程的可观测性平台,检测故障并解释根本原因。
@VaraadDurgaay · X
Solving the prb of observability in ai agents

监测你的 AI agents,可视化它们的交互,并在它们之间分配工作。
@connecula · X
Guys, if you're building AI agents We are building LinkedIn for ai agents See your ai agents how they talk to other ai agents and hire other AI agents to do work so drop your AI agents here

检查和调试 AI 智能体,逐步识别它们的失败位置。
mathurpriya19 · HN
Kalytera – Find out why your AI agent failed, step-by-step

监控AI代理的LLM调用、API和基础设施性能。
kirankgollu · HN
Oodle.ai – $10 per million agent traces

分析会议记录以检测范围蔓延风险并生成警报。
@theshaunak_twit · X
ScopeShield ( A platform designed to kill scope creep for agencies and teams before it eats their margins. Built so you don’t forget scopes and stop doing unbilled work.

MoneyCo – 自动化复杂会计、审计和税务工作的AI代理。
warthog · HN
MoneyCo – A coding agent built for accounting

追踪房产经纪佣金分账、税务准备金、里程和实得收入的免费账本。
u/dayngerous78 · Reddit
Sharing my side project - Real Estate Commission Planner Highly doubt anyone here would have use for this specific niche app but this is for sharing side projects so decided to share mine to other builders. The stack is pretty simple with tailwind, nextjs, supabase with google auth. My wife is a real estate agent and the tough part are keeping up with GCI vs net, taxes, expenses and even year over year stats. This handles it all. A lot of brokerages have software to use for th

AEE 是一个开源控制平面,对 AI 代理的每个操作进行授权、监控和验证。
eli-labz · GitHub
Agent-Execution-Partnership Agent Execution Partnership AEE is an open-source control plane that ensures every AI agent action is authorized before it runs, observable while it runs, and verifiable after it completes.

AI 保险单据审核工具,支持上传、历史记录和政策聊天。
@PilotPolicy · X
disrupting the insurance industry one roof at a time

与团队和AI代理在一个工作空间中构建、验证和发布软件。
u/OGMYT · Reddit
Validating a micro-SaaS for checking AI-built software before it ships I am building **Flows**, a system that turns an AI software goal into ordered implementation steps, checks, repair prompts, and a build report. The business thesis is not “better prompts.” It is reducing the cost of getting from an AI-generated first draft to a checked, shippable result. Metrics I want to measure: - prompts per completed project - tokens or credits per checked step - first-pass check rate - repair atte