Octolens
Social listening for the agent era
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Octolens - Social listening for the agent era

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Your AI agents read your code, docs, and CRM but can't see Reddit, Hacker News, podcasts, or the news. Octolens is one API for every mention across the internet. AI-filtered JSON via API, webhooks & MCP. Pipe it into Slack, your CRM, your warehouse, or your agents.

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This is cool! How do you get around rate-limits, shaddow bans, and SoMe being generally inaccessible for automation, and geting stricter every day?

Maker

Thanks Andrè!

We don't do any auto posting or spamming on socials.

 Yes. but reading from SoMe websites is also restricted and notoriously difficult to keep stable. As new anti scripting initiatives are launched continously. Any inisght into how you handle this?

Congrats Charlotte! The “our DAUs went down while revenue 5x’d” story is the most honest pivot explanation I’ve read on PH in a while. I build internal AI agents for work, so the MCP route is what I’d use. One question: when I add a new keyword, do I get historical mentions backfilled or only new ones from that point? Matters a lot for competitor tracking where the old threads are half the value.
Maker

Thanks,! When you sign up or add a new keyword we go back one week historical, from then on its about the new mentions coming in.

Very cool! We've tried several similar tools because we specifically need to monitor LinkedIn, but we weren't happy with any of them. When monitoring was based only on keywords rather than semantic understanding, we ended up with thousands of post links, of which only about 0.1% were relevant at best. Does your system analyze posts based on their meaning rather than just keywords? If it processes several thousand posts per day, how much would that cost?

We're ready to become your customer if the pricing is reasonable and the analysis is based on semantic understanding rather than just keywords. We also only need support for a single platform - Linkedin

Congrats on the launch! I came across a similar product recently that was upfront about not collecting data from X and LinkedIn due to platform restrictions - and I thought that transparency was actually a smart trust-building move. Curious how Octolens handles those two sources, and whether you're open about the limitations when they exist?

the insight that your happiest customers never opened the dashboard is one of those things that sounds obvious in hindsight — rebuilding as a pure data layer is the right call. how does the MCP path handle latency, is it synchronous per-mention or batched?

Love the MCP support. Have you seen developers build autonomous workflows where an agent not only detects a relevant mention but also drafts a response or creates a GitHub/Linear issue automatically?

The "your agents can't see Reddit/HN/podcasts" framing is sharp — that blind spot is real. Question for the makers: how do you keep signal-to-noise high on broad keyword mentions? In my own outreach the hardest part was always filtering the 90% of matches that mention the keyword but have zero real intent. Congrats on the launch 🚀

Cool product, I like that there are multiple ways to get data our (MCP, Slack, API, etc), this makes it really versatile. Congrats on the launch!

Amazing product, most of all I love how it filters our non relevant mentions with AI, most competitor tools do it much worse

I tried to explore this but it is throwing an error. I can't use it with my Gmail account. I used various mails of mine but it's still not working.
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