Katalyst is the AI sales agent for teams on Salesforce. Hang up a call and it's already done: notes summarized, records created, fields updated, follow-up drafted, next step set. It runs 24/7, reading every call, email, and calendar, surfacing the right signals, prepping you for each meeting, and prompting you to act: follow up here, this one’s slipping. What's new: AI Resolution on every account, meeting recorder, hygiene scores, deal patterns. Built for enterprise sales teams.
Congrats on the launch Div!
Does Katalyst support HubSpot or is it only Salesforce- only for now?
Katalyst
@yashasvi_kothari Thanks! love that you asked! Right now it's Salesforce-only, that's where we went deep first. HubSpot's a natural next step and it's on our radar, I'll keep you posted as that develops.
This looks really cool. What problem are you actually solving here? Like, why does this need to exist?
Katalyst
@rishav_sidhu Thanks! The core problem: reps spend a huge chunk of their week on Salesforce admin instead of selling, logging notes, updating fields, drafting follow ups, planning next steps. So the CRM ends up stale and managers can't trust the pipeline. Katalyst exists to do all of that work for them automatically, from the calls and emails already happening, so reps sell and Salesforce stays accurate on its own.
Katalyst
@rishav_sidhu Adding, the reason it's possible now is that AI can finally sit in a call and actually understand what happened, who's involved, what got committed, well enough to update a CRM correctly. That wasn't true even a couple years ago. The pain's old, the ability to fix it this way is new.
Crew
isn't it risky to let an AI agent make changes to something as important as a company's sales data?
Katalyst
@ravindra_sisodia1 The agent will tell you why it's making changes and also provide suggestions. These are some of the things that will actually help make sure the agent does not do anything it's not supposed to.
Katalyst
@ravindra_sisodia1 Nothing writes silently, the rep approves changes early on, and the agent only earns autonomy field by field where it's proven accurate. High-stakes fields can stay approval-only indefinitely. It earns trust rather than assuming it.
How hard is this to set up? I know enterprise software can take forever to implement.
Katalyst
@deepanshu_bansal4 Fair concern, most Salesforce tooling is a months long implementation slog. Katalyst is the opposite: it's native to Salesforce with no middleware, so you connect your org, pick the fields you want synced, and you're live in minutes. The AI starts working your pipeline from day one. No rip and replace, no admin project.
Katalyst
@deepanshu_bansal4 Adding to Avneet, fast setup doesn't mean it's writing freely on day one, it starts in approve mode, suggesting immediately while you stay in control, and you widen its autonomy as trust builds. Quick to start, careful by default.
What's the "Zero Board" I saw it mentioned? Sounds interesting.
Katalyst
@mayank_singla4 The Zero Board is the pipeline hygiene dashboard. It shows every deal that's missing critical information: empty fields, stale next steps, overdue actions. The goal is to get the board to zero. The cool part is Katalyst doesn't just show you what's broken, it actively suggests fixes and the agent can handle many of them automatically. It turns pipeline hygiene from a painful weekly audit into something that practically maintains itself.
Katalyst
@mayank_singla4 managers tend to love the Zero Board most, it replaces the Monday round of chasing reps for updates with one screen, worst deals first. The weekly pipeline audit basically runs itself.
How does it interpret pipeline on day 90 vs real time?
Katalyst
@mallika_chawla2 Good question, want to make sure I answer the right thing, are you asking how it reads a long-cycle deal as it matures, or how it treats existing pipeline history vs. changes it tracks live?
Katalyst
@mallika_chawla2 both readings have good answers, so here's each in short. If you mean a deal that's 90 days into its cycle: nothing is read as a snapshot. Every call and email along the way has been folded into that deal's memory, so on day 90 the AI is interpreting the latest conversation with three months of context behind it, and it's deliberately careful with age, older facts still count but stale urgency gets dialed down rather than repeated. If you mean what happens when you first connect an existing pipeline: Katalyst syncs your Salesforce as it stands and pulls in the email history around each deal, so it doesn't start blind on deals that are already in motion, and from there it tracks everything live as it happens.
Could this work for customer success teams managing renewals, or is it strictly for sales?
Katalyst
@new_user___1882026b09014e561aa470a If the CS team manages renewals and expansion as opportunities in Salesforce, then yes, a lot of the value applies: pipeline analysis, meeting briefs, follow-up drafting, contact signals. The agent doesn't distinguish between a new deal and a renewal. That said, our core features and recommendations are tuned for sales workflows today. But it's a use case we're watching closely.
Katalyst
@new_user___1882026b09014e561aa470a Adding to Avneet, the renewal-slip detection is the piece CS folks tend to find most useful, catching one going quiet before the date arrives. Would genuinely like to hear how it works for your team if you try it.