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Fondo is an all-in-one accounting platform for startups. Get your books closed, taxes filed, and cash back from the IRS.

  1. 3 天前

    START: Saksham Aggarwal, CEO & Founder, Cardboard "Agentic video editor"

    Creating video is getting easier. Finishing it isn't. AI writes code and you still review it before it ships. AI makes clips now, and someone still has to assemble them into something you'd actually publish. That's the layer cofounders Saksham and Ishan are building at Cardboard. Two engineers who met in school and taught themselves filmmaking in Bangalore by studying Apple's launch films. Saksham describes Cardboard simply: it's Cursor for video editing. There's no good VS Code for video, so they're building one. You throw your clips in and give it a goal, and it hands back a first cut in minutes. Brief it the way you'd brief a junior editor. Video isn't one problem, which is what makes the editor core hard. Screen recordings need different ML pipelines than talking heads or sports footage, so a routing model decides where each query goes. They don't want to be an AI feature inside the existing editor. They want to build the editor itself. ‍🎙️ Saksham Aggarwal, CEO & Founder, Cardboard on Fondo START  ‍ 00:45 The Cursor comparison, and why editing is the product 01:10 Learning filmmaking by studying and recreating Apple's launch films in Bangalore 02:30 The YC launch that reached roughly half a million views 03:15 What WebGPU and multimodal models unlocked 04:40 Why they want to own the whole editor instead of plugging into Final Cut 05:10 AI-generated clips are a new camera—and they still need editing 05:50 Why video is one of AI's hardest multimodal problems 07:00 Briefing Cardboard like a junior editor 07:40 Why they stopped selling launch videos to focus on product ‍ Check out www.usecardboard.com

    START: Saksham Aggarwal, CEO & Founder, Cardboard "Agentic video editor"

  2. 6 天前

    START: Jayram Palamadai, Founder & CEO, Byteport: “Transfer data on any network 10x faster”

    30 petabytes of collider data. That was Jayram Palamadai's job at CERN, where he worked as a distributed computing engineer getting collider data out to physicists. At that scale you stop thinking about files and start questioning the protocol underneath them, so he designed a different architecture. That became Byteport. It's built on DART, a proprietary transport protocol developed by engineers out of CERN. TCP cuts its congestion window the moment it detects packet loss and then recovers slowly; DART holds near-constant throughput instead, roughly 98 Mbps on a 100 Mbps connection whatever the latency, jitter, or loss. In the field, Byteport has hit speeds up to 1,500× faster than TCP. It runs wherever critical infrastructure runs: on-premises, air-gapped, hybrid, cloud. And in those places a failed transfer isn't a file that shows up late. It's a training run stalled at the data-loading step, a satellite pass that comes and goes, a drone flying without the map it was supposed to have. Byteport runs in all of them. It holds up in intermittent connectivity, high latency, and contested RF. DART runs mission-critical networks spanning land, air, sea, and space. ‍🎙️ Jay Palamadai, Founder, Byteport on Fondo START ‍ 00:59  Byteport's faster file transfers01:13 Moving 30 PB at CERN01:24 Rethinking internet architecture01:57 Launch day reflections02:50 Driving to YC office hours03:17 Getting into YC03:45 The YC interview04:35 What's next for Byteport ‍ Check out byteport.com

    START: Jayram Palamadai, Founder & CEO, Byteport: “Transfer data on any network 10x faster”

  3. 8月10日

    START: Gaurav Maken, Community Partner, Pioneer Fund "500+ Y Combinator alumni investing in top Y Combinator startups"

    Pioneer Fund met Gaurav Maken at Y Combinator Demo Day, and today he works there as Community Partner. What stayed with him was the way the meeting ran. The people across the table were curious rather than performing, and they wanted to understand what he was building. That's carried into how Pioneer operates now. The team preps hard for every 30-minute founder meeting, several founder-investors join each call, and they'll tell a founder what they like and what they don't, because they've sat on the other side of that table and know how it feels to leave an investor meeting with "nothing". Then they hand the evaluation back. Pioneer sends a post-meeting survey asking founders how the conversation went. Many of them say Pioneer Fund understood their business better than anyone else they met while fundraising, despite some of those founders still getting a "no". Today Pioneer is backed by more than 500 Y Combinator alumni serving as Venture Partners, with 730 portfolio companies and 1,500+ portfolio founders behind it: a network of founders who stay involved long after the investment. It's still growing. VP spots mostly come through referral. And if you don't have one, reach out to Gaurav ‍ 🎙️ Gaurav Maken, Community Partner, Pioneer Fund on Fondo START pod ‍ 01:47 — How PG's essays led him to YC02:04 — Instacart in 2015, then a grocery startup02:22 — What the 2020 shutdown taught him02:52 — Starting a mental performance clinic for founders03:10 — The Demo Day meeting 03:26 — 500+ venture partners, 1,500+ backed founders04:50 — The prep behind every 30-minute founder call05:59 — The survey Pioneer sends after every meeting06:47 — Expert hours08:13 — How Jason built a system for investors09:36 — What it takes to become a Pioneer Fund VP ‍ Check out www.pioneerfund.vc

    START: Gaurav Maken, Community Partner, Pioneer Fund "500+ Y Combinator alumni investing in top Y Combinator startups"

  4. 8月7日

    START: Aram Shatakhtsyan, Founder & CEO, Modelence "Build production-ready apps with AI"

    Every startup can build a demo. Then comes everything else: authentication, databases, hosting, monitoring, email, analytics, real-time infrastructure. None of it makes the demo, and every team rebuilds it anyway. Aram Shatakhtsyan spent nearly a decade scaling a startup and kept hitting the same thing. Too much engineering went into infrastructure that looked nearly identical from one product to the next. Modelence is a production-ready framework and cloud platform for the era of AI-generated software, where developers spend their time on product logic instead of rebuilding the same foundation. Generate a full-stack app from a prompt. Auth, database, and production deploys wired in from day one. Inspect, edit, and own the code. Deploy it to Modelence Cloud with production infrastructure, monitoring, scaling, and a custom domain, without assembling a stack of separate services. Prototypes are easy. Production isn't. We filmed this episode with Aram on January 23. Since then, the AI App Builder hit #2 Product of the Day on Product Hunt, and their new Mobile Builder launched in July. "Build production-ready apps with AI" ‍ 🎙️ Aram Shatakhtsyan, Co-Founder & CEO, Modelence on Fondo START pod ‍00:57 — The scaling challenges that inspired Modelence 01:22 — Why every startup keeps rebuilding the same infrastructure 02:01 — Why TypeScript became the foundation for AI-native development 03:06 — Building the TypeScript equivalent of Ruby on Rails 03:45 — Why infrastructure matters more than another AI app builder 04:18 — The difference between prototyping and production software 05:14 — Why today's frameworks weren't designed for AI coding agents 06:03 — Designing AI systems with guardrails instead of prompts 07:16 — The vision for production-ready AI applications 08:07 — What Aram hopes developers build with Modelence next ‍ Check out modelence.com

    START: Aram Shatakhtsyan, Founder & CEO, Modelence "Build production-ready apps with AI"

  5. 8月6日

    START: Charu Sharma & Michael Mernagh, Co-founders, Fenrock AI: “The First AI Workspace for Banking Back Office”

    99% of U.S. banks aren't JPMorgan.All of them are regulated like it. The bottleneck isn't serving customers.It's everything that happens after. Loans.Compliance.Fraud investigations.Customer operations. The work keeps growing.Headcount doesn't. JPMorgan has tens of thousands of analysts.A community bank has a handful. That's the gap Fenrock AI is closing. Fenrock is building the first AI workspace for the banking back office. Built alongside U.S. bank CEOs.Designed for banks.One workspace for all of it. AI gathers the information.Organizes the evidence.Drafts the analysis.Prepares the report. The analyst reviews.The analyst decides. No rip-and-replace.No data migration. Just an AI workspace embedded into existing workflows. Every action is documented with bullet-proof audit logs.Built-in regulatory guidance.Reporting designed for examiners and boards. An analyst clears about 10 alerts a day.Fenrock is built for 20x that. Not by replacing people.By giving them capacity they've never had. Banks process more.Pass their exams.Improve efficiency ratios.And keep serving the communities that depend on them. 🎙️ Charu Sharma & Michael Mernagh, Co-Founders, Fenrock AI on Fondo START pod 01:16 — Fenrock AI's vision: AI agents for the banking back office 01:57 — Customer discovery leads from financial crime to banking compliance  02:33 — Why small and midsize banks became the focus  03:02 — Charu's early life and the experience that shaped her resilience  03:52 — Building multiple startups before founding Fenrock  04:18 — Michael's background building privacy-preserving machine learning at Apple  05:07 — Finding the right co-founder and choosing a long-term mission  06:03 — Pivoting the company and using YC to accelerate execution  07:37 — How YC raised the team's ambition and execution speed  08:36 — Building the first AI workspace for the banking back office  09:17 — Helping small banks meet regulatory expectations with AI  10:24 — Human-in-the-loop workflows, audit trails, and early customer impact Check out fenrock.ai

    START: Charu Sharma & Michael Mernagh, Co-founders, Fenrock AI: “The First AI Workspace for Banking Back Office”

  6. 8月3日

    START: Chloe Sow, Co-Founder, Infera "The operating system for your laboratory”

    Scientific discovery shouldn't slow down because of software. But every instrument in the lab ships its own, and someone has to learn all of them. Researchers don't want to memorize instrument interfaces. They want experiments to run.They want answers.They want data. That's the problem Infera is solving. Chloe Sow knows that side of it. Mechanical engineering at Harvard, research at Brigham and Women's, building medical devices and running the experiments by hand. Her co-founder Troy Cheng spent an entire research summer figuring out how to run his lab's experiments on one machine. That was the summer. So they built the thing they needed. Describe an experiment in plain English.Infera turns it into a validated, instrument-ready run across the equipment your lab already uses. One system for protocol logic.Vendor-specific scripts.Laboratory data.Inventory.Institutional knowledge. Today, running an experiment means going instrument by instrument.Tomorrow, one place for all of them. AI agents already design experiments and protocols. But nothing connects those designs to real laboratory instruments. One system.From intent to execution.‍ Infera: "Control lab instruments with natural language" 🎙️ Chloe Sow, Co-Founder, Infera on Fondo START pod ‍ 00:45 Claude Code for scientific instruments01:27 Troy's entire job was one liquid handler02:39 Every run captures a record. The missing layer between AI and instruments03:12 Scientists pressing buttons without knowing the machine04:22 Plain English to validated instrument-ready run. Academic labs and cores first05:50 Every instrument ships its own closed software06:02 Meeting at a virtual Caltech admit session07:19 Applied to YC for feedback. Got in first try08:35 Staying disciplined instead of chasing the SF event circuit ‍ Check out infera.bio

    START: Chloe Sow, Co-Founder, Infera "The operating system for your laboratory”

  7. 7月31日

    START Nasrat Khalid - Founder & CEO, Aseel “Connecting artisans to global markets and enabling transparent aid”

    You can track a burrito from the restaurant to your door in real time You donate to a family in a crisis zone. Usually you get a thank-you email. That's where it ends. Nasrat Khalid couldn't understand why. We expect complete visibility when we order dinner.Why not when we're helping another human being? So he built Aseel. A platform for "everything do good" You buy a food package. You see exactly who receives it. You can ask for a photo of the delivery.You can exchange messages with the recipients, if they choose to participate. Instead of donating into a system and hoping, you know the aid reached the person who needed it. That's the whole idea. No plane ticket. No project. No abstraction. "Award-winning US-based platform connecting artisans to global markets and enabling transparent aid" ‍ 🎙️ Nasrat Khalid, Founder & CEO, Aseel on Fondo START ‍ 00:45  The platform for everything do good02:25  The first 16 years, as a refugee02:55  Why he left institutional aid to build Aseel03:40  Leaving Afghanistan at 16 days old04:05  No ID means no school, no bank account04:35  Why identity comes before food05:15  Seven years inside the World Bank05:58  What happened to aid in Afghanistan after 202107:00  AidOS, for institutions07:40  The Uber Eats insight08:20  The $30 package you can trace to a family09:35  Why he joined the residency12:30  How to get started ‍ Check out aseelapp.com

    START Nasrat Khalid - Founder & CEO, Aseel “Connecting artisans to global markets and enabling transparent aid”

  8. 7月28日

    START Sherwood Callaway, Founder & CEO, Sazabi “Observability On Autopilot”

    AI changed how software gets built. The tools we use after we ship haven't caught up. Code is getting cheaper. Production is getting harder. That's the gap Sherwood Callaway saw after building with Cursor and Claude Code. AI had transformed how software gets built, but when something broke in production, he was back clicking through observability tools that hadn't kept pace. Sazabi is built for AI-native engineering teams. → Autonomous alerts with root-cause context→ Conversational debugging instead of endless dashboards→ AI that learns your codebase, architecture, and past incidents AI is making it easier than ever to build software. Sazabi makes it just as easy to understand what's happening in production—helping engineering teams detect issues earlier, identify the root cause faster, and get back to shipping. Observability is becoming one of the most important layers of the AI software stack. ‍ 🎙️ Sherwood Callaway, Founder & CEO, Sazabi on Fondo START pod ‍ 01:08 — Building AI-native observability for fast-moving engineering teams01:45 — Why AI made observability a much bigger problem02:07 — "Code is basically free"02:36 — Why architecture and product thinking are the new bottlenecks03:09 — "Measure twice, cut once" — how Sazabi stays focused03:35 — History major to Dev Bootcamp: turning down investment banking05:50 — Joining Brex at employee 70 through hypergrowth to $12B07:10 — Starting Brex's observability team — the seed of Sazabi07:48 — What observability actually is (it started with 1960s rocket science)09:45 — "I will leave Brex today" — the Dalton Caldwell moment12:16 — Building one of the first production AI agents at 11x13:33 — The Cursor vs. Datadog contrast that sparked Sazabi ‍ Check out www.sazabi.com

    START Sherwood Callaway, Founder & CEO, Sazabi “Observability On Autopilot”
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簡介

Fondo is an all-in-one accounting platform for startups. Get your books closed, taxes filed, and cash back from the IRS.

資訊

  • 創作者
    Fondo
  • 活躍年代
    2025年 - 2026年
  • 集數
    103
  • 年齡分級
    兒少適宜
  • 版權
    © 2026 Fondo
  • 節目網站
    START

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