Hey DEV community! I'm Baris, and I've been building SignalPosts - a tool that turns sales call transcripts into LinkedIn posts.
The problem
If you're at a B2B company, your sales team has dozens of conversations every week that are full of gold: real objections, sharp questions, win-loss patterns, and stories from actual buyers. Almost all of that disappears into a call recording tool and never gets used again.
Meanwhile, the same team struggles to post consistently on LinkedIn because writing from scratch is slow, and generic AI content sounds like... generic AI content.
What SignalPosts does
- Analyzes your sales call transcripts and pulls out the key themes, objections, and insights
- Generates LinkedIn posts from those insights, written in each author's own voice - so a rep's post sounds like the rep, not a template
- Runs everything through a multi-role approval workflow: marketing or leadership can review, edit, and schedule posts before they go live
The goal is to turn conversation intelligence you already have into a steady stream of authentic, pipeline-driving content.
Who it's for
B2B sales and marketing teams doing social selling and demand generation - sales reps, founders, and marketers who want a credible LinkedIn presence without spending hours writing.
Try it
You can check it out at https://www.signalposts.com - I'd genuinely love feedback from anyone who's wrestled with turning internal knowledge into public content. What would make this useful for your team?
Top comments (1)
Generic AI LinkedIn content is basically a meme at this point, so in-each-author's-own-voice is the make-or-break claim here. What does it learn a rep's voice from, their past posts or the way they talk on calls? The second is the harder build but the honest one, reps who never posted before have no writing voice to copy.