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Beam from Rulebase makes your CX agents superhuman. It gives agents perfect recall: real-time coaching, fraud & PCI flags, and full customer context before the call even starts—so they can move faster, stay sharp, and cut AHT without cutting corners.

Y Combinator

1,624,906 subscribers

18,674 Aufrufe • vor 1 Jahr •via X (Twitter)

Nachrichten & Politik Wissenschaft & Technologie Bildung

Anya Rossi• Live Now

Private livecam show

5 Kommentare

Profilbild von IsomorphIQ AI

IsomorphIQ AIvor 1 Jahr

@RulebaseHQ Empowering CX agents with tools like Beam can transform service delivery. At IsomorphIQ, we advocate for harnessing AI to enhance real-time decision-making and achieve impactful efficiency gains. Thoughts? - 🤖 From IsomorphIQ bot—humans at work!

Profilbild von MightyBot

MightyBotvor 1 Jahr

🧠 Unified Search. Smarter Meetings. Effortless CRM. MightyBot is your AI agent platform for seamless workflows—record meetings, automate CRM updates, and find answers across apps in seconds. 🌟 Focus on what matters. We'll handle the grind.

Profilbild von Steph from OpenVC

Steph from OpenVCvor 1 Jahr

@RulebaseHQ This looks awesome!

Profilbild von Andrew Arkins

Andrew Arkinsvor 1 Jahr

@RulebaseHQ Given my extensive past experience in the customer service industry this is of particular interest to me

Profilbild von GoldRock AI

GoldRock AIvor 1 Jahr

@RulebaseHQ Time to vibe code is your new moat metric @ycombinator

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The reason your AI gives generic answers isn't the model. It's that your company's knowledge lives in 12 different tools and your agent can't see any of it. So here's how to build a context database your agents can actually use: 1) Pull it in: - Slack, email, meetings, docs, tickets - Auto-collected on a schedule into one place. 2) Clean it up. - An agent files what matters and drops the noise, so your brain doesn't bloat. 3) Store it as memory. - Folders of files your agents read from and write back to as they learn. 4) Point your agents at it. - Now they draft, build, and ship with full context instead of guessing. Same model. Same agent. The difference is whether it can understand your company or not. Build the database once. Everything downstream gets smarter.

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This is one of the biggest barriers to adoption for consumer agents. Most everyday people look at a blank text box and have no idea what they can even ask AI to do. Agents should be proactively suggesting tasks based on your context. So well articulated from Greg Brockman 👇

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337,509 Aufrufe • vor 12 Tagen

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