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.
As someone working in a Communications and Strategy space, does Katalyst account for constant changes and updates to a singular project or task? How does it take into consideration for the different asks from stakeholders at various points in time?
Katalyst
@anagha_nair Love this question. Short answer, yes: Katalyst treats a deal as a living thing, not a one-time entry, updating off every new call, email, and meeting, and preserving each stakeholder's ask with attribution instead of overwriting. Curious what you're picturing though, since we're Salesforce-native today, are you thinking sales opportunities or broader project and stakeholder tracking?
Katalyst
@anagha_nair Really thoughtful question. Katalyst is built specifically around sales deals rather than general projects, but the problem you're describing, one long-running thing that keeps changing shape as different people weigh in, is exactly what a deal is, so it's the core thing we handle. The way it works: every new conversation gets read against everything that came before it, not in isolation. So when a stakeholder changes an ask in week six, the AI sees that against what was said in week one, updates the record to reflect the new reality, and queues the follow-ups that fall out of the change. Nothing is ever a frozen snapshot, the current state simply evolves as the conversations do.
And each ask stays tied to the person who made it, so when three stakeholders want three different things at three different times, that history lives on the deal rather than in someone's memory. One principle we baked in that you'd probably appreciate from a comms angle: facts age well, urgency doesn't. Old information stays as context, but the AI won't keep pushing last month's priority as if nothing has moved since. If your work lives in Salesforce, this would translate directly. If not, the honest answer is we're deal-shaped today.
Katalyst
@thys_beesman The biggest challenge could be that teams are probably not okay with agents taking full control of salesforce or updating it. However, Katalyst has an agent that provides suggestions and is fully controlled so that only what needs updating gets changed.
Katalyst
@thys_beesman Building on Yajwin, the real barrier is control, not capability. Reps don't doubt the AI can update Salesforce, they doubt handing off something their number depends on. So trust is earned field by field: it suggests first, shows its reasoning, and takes on more only once it's proven accurate.
Quick question - does Katalyst prioritize which deals I should work on first? I've got 40+ opps and honestly half the time I'm guessing where to spend my day.
Katalyst
@tanay_gopal_agarwal Yes! The Katalyst agent builds intelligence on your pipeline and prioritizes deals based on size, close-date, activity, relevance and even suggests actions to take.
Katalyst
@tanay_gopal_agarwal To add, with 40+ opps the problem isn't effort, it's knowing where to point it. Katalyst ranks the list by what actually matters, size, close date, real activity, so you open your day to a prioritized view instead of guessing, plus the next action to take on each. Less staring at the pipeline, more working it.
The post-call automation flow is really sharp. Knowing the moment you hang up the notes, fields, and follow-up are already handled feels like the kind of thing reps would actually trust instead of fighting against.
Katalyst
@kayraaksaray that moment right after you hang up is the one we obsessed over 🙏 and you nailed it, reps don't fight automation that takes work off their plate, only the kind that adds a step. appreciate you.
Katalyst
@kayraaksaray You put your finger on the whole design principle, reps only fight automation that adds a step, never the kind that clears their plate. Landing the notes, fields, and follow up the moment you hang up is exactly that, work removed, not added. Appreciate you 🙏
Pipeline hygiene is the silent killer of B2B sales teams — an agent that actually works the CRM instead of just logging into it is the right framing. How does it handle reps who don't trust automation touching their deals?
Katalyst
@medal411 Appreciate that framing 🙏 the skeptical reps are honestly who we built for. Nobody hands over control on day one, it starts in approve-mode, shows its reasoning on every write, and reps only loosen up on what it's proven on. The resistant ones tend to convert hardest once they see it get their deals right.
Curious how it handles calls when reps have thick accents or talk over each other, does the summarization still hold up or does it need cleanup? Also wondering how it decides which fields to auto-update without butting into the rep's manual edits.
Katalyst
@cemrediuc On audio: holds up well on normal crosstalk, but I won't oversell it, tough audio or heavy accents can still need occasional cleanup, and since the summary shows its source you can catch anything that drifted. On fields: it never fights manual edits, you scope what it can touch and it runs in approve-mode early, so it fills gaps rather than overwriting what you've entered yourself.
How does Katalyst distinguish between meaningful sales signals and routine activity to ensure its recommendations improve deal outcomes instead of creating unnecessary noise for sales teams?
Katalyst
@satyam_raina1 It scores signals by how much they actually move a deal and how time-sensitive they are, so a new decision-maker or a slipping renewal surfaces while routine logging stays quiet. And since it runs on each rep's own pipeline, relevance is tuned to their deals, not a blanket rule.
Katalyst
@satyam_raina1 To add, the noise problem comes from tools that treat every event as equal, Katalyst scores by deal impact and urgency instead. A new decision maker or a slipping deal rises, routine activity stays quiet. And because it runs on your own pipeline, relevance is tuned to your deals rather than a one size threshold.