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Ruby knows your offerings, your customer's business, and everything that's happened in a deal — then runs the right plays, generates expert-level content, and coaches every rep like your most tenured seller.
TRUSTED BY HIGH-PERFORMING SALES TEAMS AT
WHAT RUBY DOES
Ruby AI Features to Close Smarter & Faster
Ruby builds a deep understanding of your business and develops the perfect strategy for each customer. You develop customer acumen, align your offerings to their business, and accelerate the deal cycle.
Pain & Value Positioning
Objection Handling
Competitor Strategy
Ruby automatically deploys a multi-agent deal support team after each customer interaction, without prompting. You instantly have an updated sales strategy, a stakeholder map, and clear steps to win the deal.
Next Best Actions
Risk & Mitigation Plan
MEDDPICC Scorecard & Actions
Ruby automatically generates content automatically, deeply tailored to the customer, based on reality and shared memory. You win the customer's trust by showing you understand their business and how you will help solve their problem.
One Pagers
First Call Decks
ROI, PoC Plans and Proposals
Ask Ruby anything about your account and get a real answer, rich with context and memory. You have a brilliant sales assistant ready to draft emails, create new content, and strategize on next moves.
Post-Meeting Follow-Up
Custom Materials (ABM, White Papers etc.)
Deal Thinking Partner
HOW IT WORKS
Context is Everything
Generic AI and existing sales AI solutions all suffer from a lack of context. They don't understand what you sell, why your customer buys, or how to win the deal. Ruby fixes that.
THE PROBLEM WITH AI TODAY
Why AI tools are falling short for sales teams
Current AI tools weren't built for sales. They're missing the context, structure, and proactivity that actually moves deals. Ruby was built from the ground up to fix this.
AI doesn't know your world
Generic AI doesn't know your product, your customer's business, or the right moves to make next. No real context means weak, generic output — no matter how well you prompt.
Results depend entirely on the user
Each rep runs their own AI workflow, prompts their own way, and organises results themselves. There's no consistent, applied AI experience across the team. A few figure it out. Most don't.
Chat interfaces don't scale to deals
A chat window is not a deal management system. When you have hundreds of accounts and dozens of active deals, your insights vanish into a jumble of disconnected conversations.
Nothing happens until you ask
AI waits to be prompted. It isn't running autonomously after every call, updating your deal strategy, flagging risk, and preparing your next move. That still falls entirely on the rep.
WHAT CHANGES
What changes when every
deal leverages Ruby
Most teams are doing this manually today — or not doing it at all.
Ruby automates the entire workflow.
INTEGRATIONS
Works with the tools
your team already uses.
Ruby plugs into your existing stack. No ripping and replacing. No behavior change required from your reps.
Hubspot
Gong
Zoom
Google Meet
Fireflies
Fathom
Granola
Outlook
Google Calendar
Slack
Salesforce
Soon
Microsoft Teams
Soon
TESTIMONIALS
What sales leaders are saying
Don’t just take our word for it — hear what sales leaders have to say about Ruby.
"Ruby cut our AE ramp time in half. Every rep walks in with a full strategy, sharp questions, and competitive positioning — in minutes".
Axya
Adam Lebel, VP Sales
"What used to take our team hours, Ruby now delivers in seconds. Their strategy generator and deep company insights helped us close our largest deal this year. It feels like we have a full strategy team built into our workflow."
Zain Khan
Co-Founder, Superhuman
"Ruby's instant intelligence accelerated building our ABM machine. We can source perfect contacts, business use cases and compelling events at scale. It's generated new deals with senior execs faster than any of our previous AI efforts".
InfinitySPM
Philip Kaszuba, Founder
"Ruby's meeting briefings help my team run exceptional first meetings by uncovering ideal use cases and recommending perfect discovery questions. We are making great first impressions and establishing credibility early."
