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.
What's the right plan for a team of around 15 reps and 2 managers?
Katalyst
@mehtabbir_singh For a team that size you'd be on our team plan, which scales cleanly across all 17 seats with admins getting the pipeline hygiene and deal pattern views on top of what reps see. Best move: start the free trial (up to 5 users for a month) with a few reps and a manager to feel it on your real Salesforce data, then roll out to the full team. Happy to walk you through pricing directly at joinkatalyst.com.
Is this only for Salesforce? What about companies using other CRMs?
Katalyst
@anant_tantia Salesforce-only for now, that's where we went deep first. Other CRMs are a natural next step and on our radar, but I'd rather do each one properly than half-support a bunch. Which CRM are you on?
@divyansh_lohia We use SAP. But makes total sense with Salesforce being a CRM at core.
Do you plan to introduce the AI functionality accross other ERP platforms for operational and other modules ?
Katalyst
@anant_tantia Great question. The core idea, an agent that keeps a system of record current straight from real activity, isn't specific to CRM, so extending it to ERPs like SAP and other operational modules is very much the long-term direction. We're deliberately going deep on Salesforce first because it's the sharpest and most universal pain, rather than spreading thin too early. That said, SAP is a world we'd love to understand better, so I'm curious which module or workflow eats the most manual time on your side.
Who gets the most value from Katalyst today? AEs, Sales Managers, RevOps, or someone else?
Katalyst
@esha_gosalia Honestly, everyone in the revenue org gets something, but the AE gets the most by far. They're the ones Katalyst sits with all day: it preps their calls, writes their CRM updates, drafts their follow-ups, and tells them what needs attention each morning. That's hours back every week for the person with the least time to spare.
Managers and RevOps win right behind them, because when reps stop hand-updating Salesforce, the data actually gets good. Managers see real pipeline instead of stale fields, and RevOps stops chasing hygiene. But that only happens because the rep loves using it, so rep-first is the whole strategy. Win the AE and everyone upstream benefits automatically.
That queue-with-the-error behavior is the right call, way better than a false green check. The thing I'd poke at: a bounced suggestion can sit in the queue while the underlying opportunity keeps moving, another call gets logged, someone edits the stage. So when the rep finally fixes the value and accepts, are you re-deriving the suggestion against current Salesforce state at accept-time, or writing the value as computed when the suggestion was first made? We got burned by the second version once, wrote a technically-valid but stale field.
Where do your buying signals come from?
Katalyst
@divija_diwan Great question. The buying signals come from live web and news search keyed to each account and its contacts, not a static feed. They're classified into types reps actually care about, funding, hiring, leadership and contact changes, partnerships, acquisitions, expansion, and more, and each rep picks which ones matter to them. Your own Salesforce and call activity then gets layered on to interpret what a signal means for that specific deal.
Katalyst
@divija_diwan They come from your own conversations, the calls, emails, and calendar on each deal, not a bought intent feed. A signal is something that actually happened (a stakeholder gets added, a timeline gets floated, a thread goes cold). Curious which signals you lean on most today, that shapes what's most useful to surface.
Katalyst
@divija_diwan Buying signals in Katalyst come from public news about the companies already in your pipeline. Twice a day on weekdays, Katalyst scans for fresh coverage of your accounts, funding rounds, leadership changes, hiring pushes, acquisitions, partnerships, product launches, expansion news, then classifies each one, scores it for priority, and pins it to the account and deal it belongs to. Two things we were deliberate about: every signal links back to its source article, so you can read the actual news instead of trusting a summary, and you choose which types matter to you, so it stays curated rather than becoming another feed to ignore.
How is the hygiene score calculated?
Katalyst
@taranjeev It's a weighted rollup of the signals that usually predict a deal going stale: [no activity in X days], [missing next step], [past-due close date], [stuck in stage too long]. One number, 0-100. Curious what made you ask, are you tracking hygiene manually today?
Katalyst
@taranjeev To add the mechanics, it starts at 100 and deducts for the things that predict a stale deal, past due close date, no activity in 30 days, missing next step, empty amount or account. One 0-100 score, and admins can tune which rules count and how much each weighs, so it reflects your team's definition of clean rather than a fixed formula.
How does this fit alongside salesforce?
Katalyst
@saakshi_rajgarhia Katalyst sits on top of Salesforce, not instead of it. We sync your opportunities, contacts, and activities in from SF, then layer AI on top: auto-drafted follow-ups, field update suggestions, activity logging and write everything back into SF. Salesforce stays your system of record; if a write back to SF fails, we don't update our side either, so the two never drift out of sync.
Practically: no rip-and-replace, no re-training your team on a new CRM. Reps keep using Salesforce as the source of truth. Katalyst just does the busywork around it which involves drafting the follow-up, catching the field that should've been updated after a call, logging the activity nobody had time to log and the moment a rep accepts a suggestion, it's written straight into SF.