Hi, I'm Div, Founder & CEO of Katalyst. At Datadog, I watched our best enterprise reps closing multi-million-dollar deals - lose hours every week to work that had nothing to do with selling. Updating Salesforce, prepping for QBRs, rebuilding context that already lived in an email or a call recording. The people best at selling were spending the most time not selling. I couldn't unsee it. So we've spent the last year building Katalyst to fix it: working hands-on with sales leaders and reps across teams like Stripe, Atlassian, Justworks, Datadog. Katalyst is an AI sales agent for teams on Salesforce. It runs 24/7, reads your calls, emails, and calendar, and turns it into action: - Salesforce records created and fields updated on its own - The right signals surfaced (across 10k, hiring, contact tracking, partnerships) - Account plans created, contacts researched - A brief ready before & after every meeting - The follow-up drafted and the next step set ✨ We've built Katalyst to work with your existing Salesforce set-up! What’s new: - AI Resolution on every account: like claude cowork, take deep actions on every deal with the Katalyst Agent - Pipeline with Kanban view, group by and custom views - Katalyst meeting recorder - joins meetings across Meet, Zoom, Teams, Webex - Slack bot - push updates, signals, actions to take - Actions overview - Review and take pending actions, plus bulk actions And it's already working. Mike, Sales Director at Aniai, has his reps taking 20% more meetings a day, walking in fully prepped, and moving deals to contract 50% faster - all while Salesforce stays clean on its own. @mike_conway - "If you're not using Katalyst, you are missing out on opportunities your competitors will find." We just opened Katalyst to the public. If your team runs on Salesforce, you can sign up or book a demo. Would love your honest feedback. 👇 P.S - A huge shoutout to the tens of beta customers without whose love and feedback we wouldn't be here. Also to the elite Katalyst engineering and product team!

Hey Product Hunt! 👋 Dave here, founder of Sales Stack. Excited to share what we've been building. The problem: If you've ever tried to build an automated prospecting workflow, you've probably hit the same wall: 4 or 5 different tools for lead gen, enrichment, scraping, and LinkedIn data. Each with its own API key, its own subscription, and its own stale database. None of them were built for AI agents to consume. They were built for humans clicking buttons in dashboards. Sales Stack is one console with 5 data engines, built JSON-first for AI agents: - 🔍 Lead Generation: Search 300M+ profiles by seniority, industry, department, and more - ✨ Data Enrichment: Turn a partial email or name into a complete profile - 🌐 Web Scraping: Clean markdown/HTML from any URL, with proxy + dynamic rendering - 💼 LinkedIn Intel: Pull profile data, company info, and post engagement - 🤝 LinkedIn Automation: Visits, connection requests, and messages Why it works: No API keys. Add it as an MCP server to Claude Code or Codex, sign in with email + 6-digit code, and just ask in plain English: "Find VP-level sales leaders at SaaS companies." Your agent picks the right engine and returns structured JSON. Real-time data. No stale, pre-built lists. 300M+ profiles searched live. Pay-as-you-go, credits never expire. From $0.10/credit down to $0.06/credit depending on volume. You only pay when you actually use it. Free credits included on signup, no card required. Fast. Less than 3s average response time. Fast enough for real-time agent workflows. How we make money: Credits. That's it. No subscriptions, no hidden tiers, no upsells. Buy credits, use them whenever, and they never expire. The cheapest action is a web scrape at 1 credit ($0.06 to $0.10). The most expensive is LinkedIn automation at 10 credits. Special for Product Hunt: We've set up extra free credits for anyone coming from today's launch. No card needed, just sign up and start exploring. Works with: Claude Code (MCP), Codex (MCP), Clay (REST API), any MCP-compatible or REST client. I'm here all day and happy to answer questions about the architecture, pricing model, data sources, or anything else. Would love your feedback! — Dave