5.13.2025

Announcing the Application Layer AI Camp Cohort

Jordan Crook

Almost exactly one year ago, we loudly proclaimed that the market dynamics were such that value would start to accrue at the application layer of the AI ecosystem.

This was not just by virtue of wicked competition at the foundation layer (which would flatten access to the underlying technology and speed up its advancement), but also by the maturation of the tooling and infrastructure layers of the ecosystem.

“We see AI as a phase change in technology akin to the birth of the internet,” we wrote. “And, just like the internet, the services and products built on top of it can form wave-like patterns — replicating existing workflows, augmenting those workflows, and ultimately paving the way for truly native experiences.”

In the back half of 2024, we invested in nine incredible companies building native experiences in AI, from products that turn designers into coders, to AI for collaboration across massive IT/ERP projects, to the AI-native ‘LinkedIn for gen Z.’

We learned a ton.

We learned that increasing test-time compute, and other techniques that increase the aggregate reasoning capabilities of AI systems (improved CoT, self-consistency sampling, better RL, etc.) would act as a force multiplier against all the things we care about at the application layer (like resilience, flexibility, the ability to self-improve). We learned that innovation at the interface level has only just begun.

This led us to the App Layer thesis; a doubling down on AI-powered applications and a refinement of that thesis that has pushed us toward the future of work, productivity, automation tools for SMBs, and the overall disruption of antiquated vertical industries.

This cohort is made up of nine teams that are harnessing rapidly improving foundation layer capabilities with purpose built design and architecture; building products that deliver value quickly to a well-defined user profile.

Our co-investors in this cohort include Slack Fund, True Ventures, and Fermont Capital. App Layer Camp is proudly sponsored by Mercury.

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So, without further ado, meet the teams:

Decode

A whiteboard for your ideas that writes software for you.

getdecode.dev

Betaworks POV

It’s pretty obvious that language models are getting better at the mechanics of coding every day. Our initial attraction to Decode was rooted in their approach to the interface of programming, rather than the code-gen itself. Their vision is some of the most maximally visual and spatially aware approaches to creating working code that we have seen, one that takes full advantage of the visual and conceptual understanding capabilities of the latest multimodal models. They bring years of practical experience to making the tool that they themselves want.

Problem

‍AI code generation lacks context from scattered product requirements across Notion, Figma, and Miro, creating friction and disconnected conversations.

Solution

IDE-integrated whiteboarding app for organizing requirements, creating wireframes, and generating code using AI that understands all inputs.

Team
  • Francois Laberge (CEO): 20+ years building developer tools
  • Sriraam Raja (Founding Engineer): AI/learning tools expert, Harvard masters at intersection of AI/technology and education
Target Customers

Product-minded developers who both design and code — frontend and design engineers.

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Trampoline AI

Complex RFP response management for service companies

trampoline.ai

Betaworks POV

We actually met the Trampoline team over a year ago when they were building a universal search tool for businesses. But it wasn’t until Q4 24 that they had found strong PMF from their sales-oriented users. They realized that they could take the power of their self-improving architecture, combine it with some of the most powerful UI primitives from the web 2.0 era, and unleash LLMs on the highly complex process of answering RFPs within an organization. Not only are they providing strong value to voracious customers, but they are organically solving the context problem of large projects with collaborative (and literal) building blocks.

Problem

Service companies struggle with complex RFPs requiring significant time and stakeholder coordination, especially challenging for SMBs competing against larger firms.

Solution

AI-powered platform automating RFP response process, saving 30–80% time while improving win rates through intelligent task management and knowledge base maintenance.

Team

Target Customers

Service and tech companies selling to government/large corporations, including IT consulting, architecture, and maintenance services.

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TabTabTab

AI everywhere on your computer without prompting.

tabtabtab.ai

Betaworks POV

At Betaworks, we are obsessed with the idea of removing barriers to using AI, and when we met the TabTabTab team they had actually built something that many of us had been dreaming about for a long time. Sometimes, removing those barriers means building software that lives on the client, so that it can sit on a layer above the operating system and all the other applications you use. What that actually means in practice is that TabTabTab has built a product that is invokable in milliseconds, can respond to your keyboard and mouse instantly, and has awareness of everything that you, as the user do. From there, they can build products that truly can fit into every part of your workday and workflow. This is one where watching the demo really helps to understand the total possibility space.

Problem

AI tools are fragmented and require constant context switching, breaking user flow and requiring manual effort.

Solution

Computer layer that seamlessly connects context from screen/clipboard/apps to AI, starting with LLM-powered copy & paste.

Team

‍Former Bloomberg engineers with experience at Palantir and Citadel, focused on human-computer interaction.

Target Customers

‍Computer power users who frequently switch between apps, with users in 59+ countries.

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Superposition

AI recruiter for startup founders

www.superposition.ai

Betaworks POV

‍Superposition ticked several boxes for us: a founder with vast domain expertise and taste, a multimodal interface, and the ambition to not just build tools for service providers but to become the service provider. Edmund’s nuanced and opinionated approach to recruiting combined with the technical chops to successfully run a relatively complex multistep process via AI is a powerful combination that is proving highly effective for customers.

Problem

Early hiring challenges: founders manually screen thousands or use agencies that don’t understand startups.

Solution

AI agent collaborating on hire design, candidate matching, and personalized outreach with automated interview scheduling.

Team
  • Edmund Cuthbert (CEO): 7-year recruiter, hired Brex engineer #1
  • Xiang Li (CTO): Early YC startup engineer with hiring experience
Target Customers

‍YC and Betaworks startups (Seed-Series A) hiring engineers in SF, NYC, and London.

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Hopper

Vibe planning for scalable AI coding

‍hopper.dev

Betaworks POV

Hopper is built as the result of Nathan’s and Austin’s genuine pain and frustration and decades of collective experience managing engineering teams at Amazon, Microsoft, and venture-backed startups. The velocity of scaling engineering teams is not determined by the talent of the coders, but by the efficiency of the handoffs from kernel of an idea, to PRD, to spec, to prod. And the Hopper team was ambitious and fearless enough to tell the truth: the handoff problem can’t be solved without unifying those workflows in a single tool.

Problem

AI coding tools fall short at scale, creating mismatched code in enterprise contexts.

Solution

AI planning companion guiding from idea to detailed tickets with technical auditing and organizational context.

Team

‍25+ years leading engineering teams in demanding big tech environments.

Target Customers

‍Currently in trials with companies seeking scalable AI coding solutions.

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Afterimage

Democratizing access to justice for patients

Betaworks POV

‍When Andrew Gregory told us the story of his journey to Afterimage, we were compelled both by his willingness to validate his own thesis via data — even if it meant doing things that don’t scale (like driving all over the North East to access paper medical records) — as well as his technical chops. But what really sealed the deal was his ‘stop-at-nothing’ ambition to prevent medical injustice in this country, even if it means transforming the status quo as we know it.

Problem

Millions affected by medical errors lack ways to understand incidents or seek justice, causing healthcare frustration.

Solution

Platform helping patients discover what happened and obtain justice when needed.

Team
  • Andrew Gregory (CEO): Startup founder, AI scientist
  • Peter Anderson: Leading medical malpractice attorney, Morgan & Morgan DC founder
Target Customers

‍Patients and families feeling mistreated by healthcare providers.

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JigsawML

AI-powered Cloud Management Platform

‍jigsawml.com

Betaworks POV

‍We’ve looked at a fair amount of developer tooling in the cloud management and dev-ops space. Jigsaw was the first company that we had talked to that decided to take on the very hard challenge of taking a code analytic approach to allowing AI to understand software architecture. Pracheer, using his deep experience building AWS from the early days and building what would be some of the fundamental technologies at the intersection of AI and data storage/retrieval as a founder of Pinecone, has been able to achieve impressive results.

Problem

Complex cloud management requires constant context-specific decisions despite available tools.

Solution

AI-driven visualization and management of enterprise architecture, addressing cost, security, and troubleshooting.

Team

Early AWS engineers and Pinecone founding team member with cloud/AI expertise.

Target Customers

‍Senior technology executives seeking improved team productivity and quality.

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NetAssist

NetAssist makes digital life simpler for seniors and more effective for caregivers

netassist.live/seniors

Betaworks POV

‍The super simple problem NetAssist is targeting is one that is both highly relatable (at least to me and my fellow millennials) and also highly fitting for this moment in technology, as it could only be solved in this way at this moment in time. By reanimating the OG preferred interface for senior citizens (the phone) and architecting a system that can patiently teach, perform tasks itself, and coordinate among family, caregivers and businesses serving this demographic, NetAssist looks to bring the latest in application layer services to tens of millions who have been left behind by tech.

Problem

‍America’s seniors battle a perfect storm: fading digital confidence, growing isolation, and overwhelmed support networks. As one of our fastest growing demographics, they need more help than ever while their caregivers and local services buckle under pressure. Today’s fragmented digital landscape is a maze of confusion — devices, tools, and platforms that weren’t built with seniors in mind. The stakes are high: critical services go unused, connections wither, and an entire generation risks digital abandonment while their caretakers suffer from overload.

Solution

‍NetAssist bridges the digital divide for seniors through intuitive voice and text agents that simplify complex online experiences. Our technology captures users’ needs and seamlessly guides them to solutions, local services, and community connections — while keeping caregivers involved in every step of the way.

Team

NetAssist was born after its founder played family tech support one too many times. Seeing firsthand how difficult simple online tasks were for his mother — from navigating medical systems to exploring connections in her community — he realized millions of seniors and their caregivers face these same challenges daily. The team brings deep experience building and launching new technical products across diverse markets — from Microsoft’s developer tools to AI applications for international aquaculture operations and consumer marketplaces for developing markets. The team is fueled by empathy and armed with technical expertise to lead NetAssist’s mission.

Target Customers

‍Senior citizens struggling with technology and their caregivers seeking simplified digital solutions.

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Graze Social

The toolkit for building the future of social

graze.social

Betaworks POV

‍We’ve known Devin as someone who has been working at the intersection of machine learning and social systems on the internet for years. In a very short period, while building Graze in the open, they have quickly become the most important technology built on top of both Bluesky and ATProto. Graze provides key technolgy, and importantly infrastructure that embeds algorithmic intelligence into feed creation, that reimagines how content is composed in a decentralized ecosystem, for the benefit of all users.

Problem

‍Bluesky/ATProto is the best shot we’ve had in 20 years to fix social media, but it’s still in its infancy. Developers face a high learning curve, community leaders can’t make a living, and organizations lack audience control.

Solution

Custom feeds are the new social web foundation. We provide tools, platforms and the first Bluesky-native sponsored content marketplace to help build, grow and monetize custom feeds.

Team

‍Decade of experience building tools and understanding how platforms shape behavior. Experts in making complex interfaces intuitive and scaling social web products.

Target Customers
  • Community stewards seeking control and sustainable income
  • Organizations wanting direct audience relationships
  • Developers needing ATProto tools and infrastructure
  • Creators exploring sponsored content opportunities

Learn more about the Betaworks Camp program here.

Applications for H2 2025 will open soon.

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