Launched this week
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.
The auto-drafted follow-up sounds useful but here’s my concern with every AI email sounding like AI, can reps actually tweak it or do they have to copy-paste into Gmail and rewrite from scratch?
Katalyst
@saanvi_jalan Great catch! Reps customize the drafts directly in Katalyst — no copy-paste cycle. They view the draft, edit tone/details inline, and send.
On the "AI-sounding" concern: that's exactly why the template system matters. When a rep saves past emails tagged as "contract negotiation" or "expansion play," Katalyst learns their voice — cadence, formality, length, structure. When it generates the next draft, it matches against those templates first, so the AI output inherits their actual writing style, not generic corporate boilerplate.
More templates saved = better the agent learns your team's voice. It's not "fill the template," it's "generate like this person writes."
The draft is a starting point, but the customization (the 30 seconds of tweaking) is where the rep's personality lives. That's what kills the generic AI sound.
I believe that Katalyst has a lot of products at once (reads your calls, emails, and calendar, and turns it into action) I was wondering if it makes the onboarding difficult. Which workflow do you recommend customers to try first?
Katalyst
@reda_roqai_chaoui Fair question, we thought about this a lot. Instead of dumping all the connections (calls, email, calendar) on you at signup, onboarding is guided: you walk through a short setup flow where the product, the Katalyst's own agent walks with you tells you what to connect and why, one step at a time, and you see real output from your own data as you go — not a demo, your actual first draft or first insight.
So the "lot of products" doesn't show up as a wall of settings. It shows up as a conversation: connect this, see this work, connect the next thing when you're ready. Most teams are through full setup in under minutes and already have a first AI action to react to.
If you want a specific recommendation: whichever data source has the most recent activity for your team (usually email or calls) is what surfaces value fastest, and the onboarding flow actually points you there automatically rather than making you guess.
What are the "signals" you keep mentioning? What does it mean?
Katalyst
@sanvi_tiwari Signals are the things that suggest a deal's changing, a prospect raising budget, a new stakeholder joining, activity going quiet, a renewal date approaching. Katalyst surfaces them so reps act on the moment instead of missing it.
Katalyst
@sanvi_tiwari happy to add some color here. Signals are pieces of news about the companies you're selling to: a funding round, a leadership change, an acquisition, a hiring push, a new product launch. Katalyst watches for these across your accounts so you don't have to, scores them so the ones that matter most rise to the top, and attaches each one to the account it belongs to. The point is timing. A prospect who just raised money or got a new VP is a very different conversation than one you ping out of the blue, and signals hand reps those openings while they're fresh. You pick the types of news you care about, so it stays a signal and not a feed of noise.
Is this only for tech companies or would it work for any industry?
Katalyst
@hanish_bansal Any industry where the sales team runs on Salesforce. Fintech, healthcare, manufacturing, govtech, you name it. The pain of manual CRM data entry and inconsistent pipeline management is universal across B2B sales. The AI agent works with whatever Salesforce configuration you have, regardless of industry.
Katalyst
@hanish_bansal Adding to Avneet, non-tech teams often benefit most, manufacturing and healthcare reps are in the field, not living in Salesforce, so the further you are from a desk, the more the auto-updating matters.
Dropped an upvote. quick check does it support automated contact creation if a new stakeholder hops on a zoom call?
huge congrats 🙌 @divyansh_lohia for shipping this
Katalyst
@vikramp7470 Thanks for the upvote! Yeah, that's exactly the kind of thing it handles, a new face on the call gets picked up and turned into a contact so you're not back-filling it manually later. Appreciate you.
Katalyst
@divyansh_lohia @vikramp7470 And the cherry on top, if that call surfaces a real new prospect, not just a new face, Katalyst doesn't stop at the Contact. It drafts the Account and the Opportunity too, so all three records Account, Contact, Opportunity which you cares about the most come back linked as one draft.
Nothing hits Salesforce blind though, it's a plan you review and approve, so you're always in control of what gets written to your CRM.
@divLohia you mentioned Katalyst has AI chat on accounts, sounds interesting... can you tell me more? How does this work?
Katalyst
@nikhil_motiani1 Yes the AI chat has full context of your CRM accounts and the opportunities. So while talking to AI, you can ask it questions such as what's the next best step for my account? Any many other contextual questions that are important for a deal to move forward.
Katalyst
@nikhil_motiani1 To make it tangible, you can open an account and just ask "why has this deal stalled?" and it'll pull from the actual call history, emails, and activity to answer, not a generic guess, but grounded in what's really happened on that deal. Like having an analyst who's read everything.
I am curious to know about the pipeline action recommendations- are these same as the Salesforce field update suggestions or something different?
Katalyst
@sakshi_mohta Different things. Field updates keep the record accurate, stage, amount, close date. Action recommendations are the next moves on the deal itself, follow up here, this renewal's slipping, loop in this stakeholder. One keeps Salesforce true, the other pushes the deal forward.
Katalyst
@sakshi_mohta small thing worth adding: they both come out of the same analysis. After a call, Katalyst reads what happened once and produces both kinds, the field updates and the recommended next moves, plus a drafted follow-up email when one makes sense. And accepting an action isn't just a to-do in Katalyst, it gets logged in Salesforce as a real task or event too. So both kinds end up enriching the CRM, they just start from different questions: what changed, and what should happen next.