InboxAgents - Smart Linkedin Inbox
Smart, unified inbox for Linkedin, email & social media.
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Cam McMaster

InboxAgents - Smart, unified inbox for Linkedin, email & social media.

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InboxAgents - Smart Linkedin Inbox
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Replace your Linkedin inbox. Unify it with emails and other social media platforms and chats. Have the smart inbox surface what is important to you. No need to get lost in Linkedin noise just to check inbounds.

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Cam McMaster
Maker
📌

We're launching our next MVP iteration with a core focus on replacing the Linkedin inbox because it sucks. This time we integrate 9 platforms with a new priority interface that learns your context & surfaces important matters to your attention.

Sergey Petrov

InboxAgents caught my attention. Useful direction if it stays reliable in everyday use. I care most about clear control and predictable results.

Cam McMaster
Maker

@sergeypetrov control is our focus! are you mainly interested in linkedin or were there other platforms you'd like to use?

Weiting Liu

Congrats on the launch! The early days of finding those first customers are such a grind. I remember spending what felt like half my week just on manual outreach and follow-ups. It's a tough bottleneck to break. Having gone through that recently, I've got a couple of growth experiments that might help you get initial traction without the manual slog. No strings attached, just happy to share the 1-page plan if you're interested. Keep up the great work!

Curious Kitty
Your pitch hinges on prioritization. What signals are you using to decide what’s “important” (sender identity, past replies, keywords, CRM context, revenue tags, recency, relationship strength, etc.), and how do you make that system controllable so users can trust it and avoid both false positives and missing critical messages?
Cam McMaster
Maker

@curiouskitty when the user begins, the product is quite general. it takes some info on your business and needs then constructs a prompt to start spinning up a knowledge graph & creating vector embeddings.

it is not very aggressive at first to avoid hiding things that are possibly valuable but now & again it will produce false positives. we'd prefer false positives than false negatives, but then as it obtains more context on what is important to the user, it starts getting a little more aggressive at filtering based on your personal knowledge graph.

Cam McMaster
Maker

We currently have an affiliate program where for every user who uses your code and converts to paid, you get their first month's payment. Simply go to "refer & earn" on your InboxAgents dashboard and it'll allow you to track payouts.