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- 1 weeks ago16 min
START: Nora Xiao & J Yim, Co-Founders, Rollup: "Years of user context, in minutes."
Your phone has years of context about you.Yet most new apps still start from zero.Where you go. What you eat. What you wear. How your interests change over time.J Yim and Nora Xiao saw an opportunity in all that information sitting in people's camera rolls.So they built Rollup.An SDK that turns photos into personal context, helping apps understand users without starting from scratchPhotos stay on the phone, while apps gain insights into users' interests, habits, and preferencesFor example, screenshot six bomber jackets from different brands, and a shopping app could recognize what you're looking for without asking.But the real breakthrough came when other founders started asking to buy the technology powering Rollup's original shopping app.So J and Nora pivoted from building an app to selling the underlying SDK.Just nine days later, they reported six figures in contracted ARR and seven figures in pipeline revenue.Some customers even skipped the free trial and asked to pay immediately.Their vision? A future where every consumer app becomes a personal AI, powered by a deeper understanding of its users.They started by building one personalized shopping app.Now they're building the technology that could make every consumer app personal.🎙️ Nora Xiao & J Yim, Co-Founders, Rollup, with Guest Host: Maanav Agrawal, CEO & Co-Founder, Memoir on Fondo START01:08 Meet Rollup Co-Founders J Yim and Nora Xiao02:13 Turning camera rolls into personal context03:17 From shopping app to SDK04:22 Unlocking the value of personal photos05:11 Identifying moments, trends, and shopping intent06:18 Six figures in contracted ARR after nine days07:14 Finding product-market fit08:16 The strategy behind Rollup's pivot09:12 Building a strong co-founder relationship10:21 What inspired J and Nora to become entrepreneurs12:14 The future of personal AI13:19 Expanding beyond photos14:08 Privacy, on-device AI, and user trustCheck it out at tryrollup.com
- 1 weeks ago12 min
START: Alex Kolchinski, Founder & CEO, ThunderPhone "Voice AI that nails the calls others fumble"
AI coding agents learned how to build voice AI from the internet. That might be the problem.The standard approach is simple. Transcribe the caller. Send the text to a model. Turn the answer back into speech.Three steps. Countless posts and repositories. Repeated so often that coding agents tend to reproduce the same architecture.Alex Kolchinski's bet at ThunderPhone is that the default is already becoming obsolete.Instead of one fixed pipeline, his team mixes and matches models. Sometimes several cheaper ones instead of one expensive one. Sometimes audio goes straight to the LLM, skipping transcription entirely.Every decision comes down to three competing priorities: quality, speed, and cost.Alex calls it the Ferrari approach. While other teams have good reasons to build systems that work well enough to scale, ThunderPhone focuses on squeezing more performance out of every component.And there's a catch. Alex doesn't expect that technical advantage to last forever. Foundation models keep improving, and coding agents are beginning to figure out better architectures themselves.Until then, the edge is knowing what to build differently.ThunderPhone: "Voice AI that nails the calls others fumble"🎙️ Alex Kolchinski, Founder & CEO, ThunderPhone on Fondo START 01:07 Why ThunderPhone moves beyond the standard voice AI pipeline01:42 Navigating the tradeoff between quality, latency, and price02:35 Why Storm prioritizes getting real customer calls right03:45 How software and B2B changed Alex's founder playbook04:45 Why the traditional three-step voice AI pipeline is becoming obsolete05:00 How voice AI is outperforming humans on transactional calls06:32 Why ThunderPhone isn't training its own foundation model08:15 How two founders built the platform in 6–12 months and where coding agents fall short09:30 The Model T versus Ferrari approach to building voice AI10:15 Spark at 2¢, Bolt at 5¢, and Storm at 9¢ per minuteCheck out thunderphone.com
- 2 weeks ago11 min
START: George Rose, CEO & Co-Founder, Rise Reforming "Unlocking resilience for the chemical industry"
The US produces enough biogas to make over $20 billion worth of chemicals a year60% of it is wasted or flared in low-margin applicationsIt comes off wastewater plants, farms and landfillsGas a large-scale chemical plant can't captureSo Rise Reforming goes to the gasIts modular technology fits inside a shipping container and runs on-siteThe result is the cheapest feedstock and no fossil fuels as raw materialOut come chemicals like dimethyl ether, methanol and dimethyl carbonateThat last one has no domestic manufacturer in the USThe three founders met studying molecular engineering at UChicagoThey got close over late-night problem setsEnvironmentalists turned engineers, drawn in by the chemical industry's 5% share of global emissionsThen Y Combinator, to learn how to sell chemicals1,800+ hours of stable syngas productionFirst in the Americas to produce syngas from wastewater biogasA binding biogas supply agreement and a conditional DME offtake for its first commercial unitDME is first, targeting aerosol and propane starting in 2027Rise Reforming sums it up in six words:"Unlocking resilience for the chemical industry"🎙️ George Rose, Founder & CEO, Rise Reforming on Fondo START 00:45 Supply-secure chemicals from waste gases01:45 Why centralized plants are exposed to conflicts and natural disasters02:00 Making the chemicals where the waste is actually generated02:32 Dimethyl carbonate and the lack of a single domestic manufacturer03:04 DME, methanol, and the markets Rise Reforming is targeting04:48 Environmentalists turned engineers05:32 Green premium?05:57 Price parity with the natural gas alternative06:27 A new methanol process and the cheapest feedstock07:05 Meeting cofounder at UChicago over late-night problem sets08:25 Doing YC to learn how to sell chemicalsCheck out www.rise-reforming.com
- 2 weeks ago12 min
START: Melissa Bime, CEO & Founder, Infiuss Health: "AI-Powered clinical rehearsal. Run the trial before you run the trial."
A clinical trial at Stanford enrolled a patient living in Africa.He was never physically there.He had been diagnosed with a rare genetic disorder, and Stanford was running a trial for it. The research team gathered his genetic information and medical records. They monitored him remotely and enrolled him.The patient was Melissa Bime’s father.She was working at Stanford as a clinical trial nurse at the time. She had trained as a nurse in Cameroon and moved to the US, where she worked through the COVID vaccine trials.She says that was the spark. Why not build digital versions of patients and get them into clinical trials.That’s Infiuss Health.It builds medical digital twins from real-world and historical data. Trial teams rehearse a protocol across thousands of virtual patients before a single one enrolls.The twins flag who is likely to drop out mid-study. Who has a comorbidity that affects how the drug performs. Whether two hours of travel to a research site is feasible over two years.Infiuss reports up to a 30% reduction in sample size and design cycles 10x faster.During the recent Ebola outbreak, Infiuss helped companies running vaccine trials recruit patients with a specific genetic trait.Melissa’s long-term view is approval with a hundred patients instead of thousands.Her focus is small and mid-sized life science companies. Most have one or two drug candidates the entire company hinges on. Infiuss is built to give them more tries."AI-Powered clinical rehearsal. Run the trial before you run the trial."🎙️Melissa Bime, Founder, Infiuss Health on Fondo START 01:29 From nursing school in Cameroon to healthcare entrepreneurship02:29 The diagnosis that changed everything04:22 Building computational versions of real patients05:27 Why clinical R&D costs billions and fails nine times out of ten06:23 What digital patient twins can predict today07:35 Cutting roughly six to eight months from the process08:05 Approval with a hundred patients instead of thousands08:59 A clinical trial without a control group09:50 Why smaller life science companies need more chances to fail10:21 “You shouldn’t have to go out of business ’cause you failed a clinical trial”10:55 Finding the right genetic trait during the Ebola outbreakCheck out infiuss.com
- 3 weeks ago8 min
START: Ludovic Granger, CEO & Co-Founder, Leadbay: "Qualified leads for agentic workflows"
Most sales teams are competing for the same companies. Not necessarily because they're the best customers, but because they're the easiest to find.They have LinkedIn profiles, public hiring activity, and enough online signals to show up in every prospecting database.But plenty of good businesses don't leave that kind of trail.Ludo Granger kept noticing this when visiting customers. He'd look at their prospect databases and find that he could sometimes identify roughly three times as much additional market opportunity.The companies were there. The sales tools just weren't finding them.A hotel, a restaurant, or an early-stage startup might be a perfect customer. But if it's not generating the right online signals, it can be almost invisible to traditional prospecting software.That became the problem Ludo wanted to solve with Leadbay.Instead of relying only on the signals everyone else is tracking, Leadbay tries to learn how a good salesperson evaluates a company.It looks at your business, identifies what a promising customer might look like, and uses feedback from the leads you pursue to get better over time.But Ludo isn't trying to build another database with more companies in it.He thinks the way salespeople use databases is changing altogether.During SF Tech Week, he used Claude from his car to work with five highly qualified prospects rather than sorting through thousands of accounts. Then he told the agent how to handle outreach and follow-ups.That's the distinction he's betting on. Finding more companies matters, but knowing which ones are worth pursuing matters more.Especially when the person making that first decision isn't a person anymore. It's an agent.🎙️ Ludovic Granger, CEO & Co-Founder, Leadbay on Fondo START with Guest Host: Kamran Karic, COO & Co-founder, Ploid (YC F26)01:42 Why everyone is chasing the same companies02:08 The untapped market traditional sales databases overlook02:34 How Leadbay can expand a company's addressable market02:51 Why startups should build something agents want03:17 The shift from human interfaces to AI agents03:48 How AI identifies promising businesses with limited online data04:19 Teaching AI to recognize and improve lead quality05:01 Finding five highly qualified prospects instead of 5,00005:29 Trusting AI agents to coordinate outreach and follow-ups07:04 Why qualified data is the fuel for AI-powered salesCheck out leadbay.ai
- 3 weeks ago12 min
START: Faiz Vadakkumpadath & Niyaz Puzhikkunnath, Co-Founders, Papaya "Continuous optimization for AI agents"
When everyone has access to the same AI models, what actually makes one AI product better than another?It's no longer just about the intelligence. It's about how reliably you put it to work.An agent that responds faster. Makes fewer mistakes. Delivers better outcomes for customers.That's the problem Niyaz Puzhikkunnath and Faiz Vadakkumpadath are tackling with Papaya (YC F26): continuously improving AI agents already running in production.After spending more than a decade developing their expertise at Amazon, the founders set out to build a company of their own.Their first product focused on data infrastructure. But as they began working with customers, they discovered something interesting.Customers liked the data product, but were especially interested in the AI agent harness the founders had built to make their system more reliable.Rather than asking customers to migrate their existing data infrastructure, they saw an opportunity to make that technology useful across a much broader range of applications.So they developed the harness into a standalone product, laying the foundation for Papaya.Today, Papaya analyzes how customers use production AI agents, identifies issues across prompts, context, caching, and tool calls, and opens pull requests with proposed fixes.It then tracks whether those changes actually improve quality, latency, and cost.Because knowing why your agent failed is only half the problem. Actually improving it is what matters.That's what Papaya is building toward: AI agents that get better over time, without engineers having to manually investigate and fix every issue.If you're running AI agents in production, check out what the team is building at papaya.fyi.🎙️ Faiz Vadakkumpadath & Niyaz Puzhikkunnath, Co-Founders, Papaya on Fondo START with Guest Host: Maanav Agrawal, Founder & CEO, Memoir 01:43 How Papaya identifies problems in production AI agents and proposes fixes02:49 Why fixing agents matters more than monitoring them03:02 Why companies prioritize agent quality over cost03:34 Papaya's early traction and first paying customers04:58 Automating the traditional software debugging process05:47 Why AI could eliminate the traditional maintenance phase06:18 Why identifying agent failures isn't enough06:39 Optimizing agents that power critical business workflows07:46 How Niyaz's experience debugging agents at Amazon inspired Papaya08:33 How customer feedback transformed a data platform into PapayaCheck out papaya.fyi
- 3 weeks ago11 min
START: Simon Shu & Justin Sato, Co-Founders, Restart: "The AI company builder"
How many companies die as an idea because the founder can't build the first version?That's who Simon Shu and Justin Sato have in mind with Restart, which they call the AI company builder. You describe the idea in plain language and Restart sharpens it, then builds a working web product while you watch the pages, copy, and design fill in on a live preview. It publishes to a real URL when you say so, and changes work the same way: say what should be different and watch it happen.Most people building on it are starting their first company, and most of them aren't engineers. They're making SaaS, consumer apps, marketplaces, e-commerce, service businesses, and local businesses; even a coffee shop and a restaurant right alongside apps.The whole thing started from one question: what will companies look like five years from now? Advanced AI will make companies, the economy, and society work in fundamentally different ways. In that world, what changes for workers? They should get to be creatives and visionaries, and Simon and Justin are building Restart so anyone can.Simon brings experience from Tesla and Scale AI. Justin studied CS at Stanford after doing physics and AI safety research, and he's worked in AI engineering at several startups, including Tomo. They met over poker in SF.Restart has already grown to around 50K users, largely through social, and the team keeps shipping and improving the product. There's a free plan with daily build credits, so you can start building today. 🎙️ Simon Shu & Justin Sato, Co-Founders, Restart on Fondo START with Guest Host: @peggy_wang, Founder & CEO, @sparkchat_so @digipals_app 01:40 Meeting at a founders-and-investors poker game in SF02:15 The ride home where they started trading startup ideas02:42 Building a startup always felt inevitable to both of them03:27 Moving into Justin's Stanford dorm room04:03 Grinding it out and raising a pre-seed round04:20 The starting question: what will companies look like in five years?04:55 Shipping before it's ready, and getting to ~50K users05:18 Justin's LinkedIn post gets picked up by Indian news05:35 The 20-iPhone content operation06:21 "Restart is the AI company builder."06:30 The early wedge: incorporation, payments, software07:33 Who it's for: coffee shops, restaurants, and apps07:58 What they love about SF09:24 The guests flip it: what does the host think about AGI?10:30 Simon on turning workers into creators in the AGI era11:01 Justin on Restart's responsibility to make companies AI-nativeTry it at restart.new
- Oct 8, 20269 min
START: Rodney Fong, President & CEO, San Francisco Chamber of Commerce
What does it take to build a world-class startup ecosystem?Rodney Fong's answer starts with connection.As President & CEO of the San Francisco Chamber of Commerce, he brings together founders, established businesses, policymakers, finance, technology, and the broader community - helping turn San Francisco’s density of talent into opportunity.Through YES SF, the Chamber hosts 300+ events a year, creating a physical hub where ideas, industries, and people can collide.Rodney’s philosophy is simple:Put ambitious people in the same room. Make it easier to build. Give new ideas room to grow.🎙️ Rodney A. Fong, President & CEO, San Francisco Chamber of Commerc on Fondo START with Guest Host: Grace Gong, Founder @ Smart Venture Media01:01 SF Tech Week01:48 the Chamber’s role and history02:10 How YES SF connects founders and businesses03:31 San Francisco’s comeback04:50 Why SF’s talent density matters06:10 YES SF’s 300+ annual events06:53 Why this startup cycle feels different07:35 A sea urchin startup idea08:33 Robotics and everyday automation09:13 The human side of technology
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