Korl’s Slack Agent uses AI to automatically capture and track customer feature requests – without adding new tools to your workflow. Here’s how: 1. Extracts requests from customer calls in Gong, Zoom, Fathom, Fireflies, and more 2. Routes requests for review so you can file or update Jira tickets right from Slack 3. Notifies you when features ship with a personalized update for customers It helps CSMs avoid the request “black hole” while giving Product visibility into what customers need.
I’m Berit, co-founder of Korl. Thanks for checking out our launch!
This Slack agent actually started as a hacky internal workflow we built for ourselves. We were tired of trying to remember to log Jira issues after every customer call. We were building things our customers had asked for… but forgetting to close the loop when they shipped. We knew AI could automate this, and we didn’t want yet another system to log into.
So we stitched together a rough agent that reviewed our Fathom call transcripts, flagged feature requests, and pushed them into Slack for quick triage.
Then one of our customers saw it and asked, “Can we have that?” That’s when we realized this should be part of our product, not just an internal tool.
Today’s launch is that productized version. It:
• Captures feature requests automatically from call recordings
• Routes them to Slack so CSMs or Sales can add or update Jira issues from Slack
• Tracks progress and drafts personalized updates when features ship
We’d love to hear from you. What’s your current process for tracking customer requests? And what would make this agent more useful in your workflow?
Thanks again for your support and for being part of the Korl community!
@berit_hoffmann Tracking and fulfilling customer requests directly in Slack is perfect for customer success teams! Keeping everything in one place reduces friction and speeds up response times.
How does the agent prioritize feature requests when multiple customers ask for similar things? Are teams able to connect this to product roadmap tools for seamless workflows?
The AI component could be huge for identifying patterns across requests.
This is definitely useful. A lot of customer complaints are about not getting quick responses and no one taking charge.
Korl hits a major pain point for CS/AM teams: the grind of turning scattered product + customer data into polished, personalized decks and renewal materials. Rather than wrestling with spreadsheets, Jira tickets, Slack threads, and having to build each customer‑specific slide by hand, Korl pulls everything together and auto‑generates meaningful presentations.
I especially like that it doesn’t treat “presentations” as generic templates — it builds them around real context: who the customer is, how they use your product, what their priorities are, and what value you’ve delivered or could deliver next. That shift from generic to personalized is where automation actually adds value.
For startups or small SaaS companies that can’t justify a full‑time CS ops or presentation builder, Korl seems like a tool that lets you punch above your weight: better customer communications, stronger renewals, and more consistent value messaging without scaling headcount.
That said — the real test will be how well the “AI + data sync → presentation” pipeline handles edge cases, complex data, and constantly evolving products. If that holds up, I think Korl could be a game‑changer for customer-facing teams.
Cool. And finally, do you allow the presentations to be exported to different formats?
Impressive launch, Korl team. From a clarity & onboarding lens: when a customer-facing team opens Korl for the first time, what’s the one belief you want them to hold in the first 10-15 seconds? Is it: • “I understand each customer’s unique value path, not just their usage data.” Or: • “My presentation will reflect their brand, context, and issues—no generic slides.” Because in tools aimed at personalization at scale, the biggest adoption barrier isn’t features—it’s belief that it gets the customer, not just the data.
Beautiful launch Berit. Korl feels simple and powerful. Congrats to you and the team.
Oof, this hits my “where’d that request go?” panic before QBRs. Pulling asks from Gong → Slack/Jira then nudging when it ships… nice. Also into the auto-deck angle. Curious how well it de-dupes and maps to existing tickets.
Hey ProductHunt! 👋
I’m Berit, co-founder of Korl. Thanks for checking out our launch!
This Slack agent actually started as a hacky internal workflow we built for ourselves. We were tired of trying to remember to log Jira issues after every customer call. We were building things our customers had asked for… but forgetting to close the loop when they shipped. We knew AI could automate this, and we didn’t want yet another system to log into.
So we stitched together a rough agent that reviewed our Fathom call transcripts, flagged feature requests, and pushed them into Slack for quick triage.
Then one of our customers saw it and asked, “Can we have that?” That’s when we realized this should be part of our product, not just an internal tool.
Today’s launch is that productized version. It:
• Captures feature requests automatically from call recordings
• Routes them to Slack so CSMs or Sales can add or update Jira issues from Slack
• Tracks progress and drafts personalized updates when features ship
We’d love to hear from you. What’s your current process for tracking customer requests? And what would make this agent more useful in your workflow?
Thanks again for your support and for being part of the Korl community!