用 Jev 做 GTM 信号过滤：500ms 内分出真信号与噪音

Ashwini @AshwiniNK21原推发布于 2026.09.22

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Two tools. Both named Clay. Both funded startups. Both showing up in your alerts. Only one of them matters to you. In GTM, signals are everything. A competitor mentioned in a community thread. A prospect asking the right question. A brand mention that could turn into a conversation. Miss the signal and you miss the moment. The window closes. Someone else gets there first. The problem: your alerts are full of noise. Few more examples: • Apollo - the outbound sales platform or the GraphQL framework. • Rippling - the HR tool or "rippling effects" in every economics article. •Pitch - the presentation tool, a sales pitch, or a football pitch. See..No easy tell. Just alerts that look real until you actually read them. And while you're skimming noise, the real signal is sitting unread. So I built a simple workflow using Jev to fix this for you. Two versions. Version 1 - Signal Sifter: paste your alert snippets, describe what you're actually tracking, and Jev classifies each one in under 500ms. Real signal or noise. Clean output. No setup. Version 2 - the automated one: connect your alerts feed, and only the mentions that actually matter land in your Slack DMs. Everything else filtered before it reaches you. Felt almost too simple when I first thought of it. Then I remembered I actually do this manually every week. That's usually the sign it's worth building. Links below for both the versions below!