The Series A startup that taught sales teams to fail in front of a machine first - and made $1M in monthly ARR doing it.
She has been on the job for nine days. The voice that answers belongs to a fictional procurement lead named Marcus, who has a quarterly target, a budget under pressure, and a small but believable irritation in his tone. He interrupts her on the second sentence. He asks why she is calling on a Tuesday.
None of this is hypothetical. The call is happening inside Hyperbound, the San Francisco startup that has spent the last two years convincing some of the largest sales organizations in the world that the cheapest cold call is the one your customers never have to hear.
"Sales coaching has always been one-to-few. We are turning it into one-to-everyone." - Sriharsha Guduguntla, CEO
By 9:22 she has hung up. The AI has scored her opening. Her manager will read a transcript before lunch. No real customer was harmed in the making of this practice.
Led by Peak XV with Snowflake Ventures, YC, Roble, Fellows Fund.
Achieved through founder-led sales, no outbound team.
Reported reduction in new-rep ramp time across enterprise customers.
Headquartered in San Francisco; hybrid engineering.
Most enablement software is a video library and a dashboard. Hyperbound is closer to a flight simulator. The platform ingests sales call recordings - typically from Gong or a similar conversation intelligence tool - and uses them to construct AI buyer personas that talk back. The personas come with backstories, budgets, objections, and the small human texture that breaks rehearsed scripts. New reps practice on them before they touch a live pipeline. Veteran reps practice on them before high-stakes renewals.
Cold calls, discovery, demos, renewals, in multiple languages. Tailored to your ICP, your verticals, and your favorite objections.
Auto-evaluates recorded calls against custom rubrics. MEDDIC, SPICED, Sandler - or your own.
Certifications, drills, and skill libraries that meet new hires where they are - and refuse to let them coast.
Run candidates through realistic call simulations to see how they handle pressure before they ever sign an offer letter.
Coaching scales beyond the eight people a frontline manager can listen to. Closer to eight hundred.
Pulls signal from existing call recording, CRM, and enablement tooling. No rip-and-replace.
Sriharsha Guduguntla and Atul Raghunathan grew up in the same Bay Area suburbs, traded Paul Graham essays in high school, and ended up at two of the most prominent AI teams in enterprise software. Sriharsha worked on the conversational AI behind Salesforce Einstein. Atul built ML personalization systems at Meta Ads that helped target billions of impressions a day. Hyperbound is what happens when those two skill sets aim at a problem that has resisted software for thirty years: actually getting humans to sell better.
Full-stack engineer and designer. Founding engineer at Bloom (YC W21). Salesforce Einstein. UC Berkeley RISE Lab. Spends his weeks on customer calls; spends his weekends thinking about them.
AI engineer and language model researcher. Built large-scale ML systems at Meta Ads. The person who turns voice quality, latency, and persona realism into something a sales manager will pay for.
From a YC seed in 2024 to a Peak XV-led Series A in September 2025, Hyperbound's cap table has gathered the firms that tend to follow category-defining sales software. Snowflake Ventures came in for the data story. Y Combinator stayed in. The round closed after Hyperbound had already cleared the year-end projections it had pitched on.
Hyperbound's customer list reads like the second page of any modern enterprise procurement spreadsheet - in a good way. These are the companies whose sales teams take onboarding seriously enough to buy a simulator for it.
"The cheapest cold call is the one your customer never has to hear."Internal aphorism, Hyperbound HQ
$15M Series A led by Peak XV closes. Snowflake Ventures, YC, Roble, and Fellows Fund participate. Capital earmarked for call scoring and learning modules.
Released multi-language AI roleplays and a discovery-call demo featuring an AI CRO persona pushing back on a live demo.
Public launch out of Y Combinator's W24 batch. AI sales roleplay category gets its first dedicated platform.
The category Hyperbound is building did not exist when Sriharsha and Atul started writing code. Sales coaching had calcified into two extremes - a video the rep watched alone at 1.5x speed, or a roleplay session on Zoom where the manager played a customer who, transparently, was their colleague. Neither one resembled the real act of talking with a stranger who can hang up.
Voice models got good enough to fix that around the same time that GTM teams started looking for productivity gains that did not require firing people. Hyperbound landed in the middle of that shift. Enterprises tried it because the math is straightforward: if a new rep ramps even one month faster, the platform pays for itself before the first commission check.
That is also the part that interests investors. AI products that prove their ROI inside a single quarter are rare. Sales practice happens to be one of them.
Sriharsha roleplays with an AI CRO persona inside the platform.
How elite sales teams train with AI - with the CEO on CoachEm's podcast.
A long-form interview on how the platform is built.
Full library of product walkthroughs on YouTube.
This time Marcus is in a hurry. He asks her to email him instead. She does not flinch. She has heard that line forty-seven times this week, every one of them inside Hyperbound, and she has a clean handle for it now. Marcus stays on the call.
The interesting thing is what is not happening. There is no manager listening in. No senior rep on the bench. No customer with a logo on their badge being treated as an opportunity to learn from. The training has already happened. The call is just the proof of it.
Two years ago, that practice loop did not exist. Hyperbound is the company that built it - quietly, profitably, and at a speed that surprised even the firm that led its Series A.
"They hit their end-of-year targets before we'd signed the term sheet." - paraphrased, Series A investor