Penguin Ai Accelerates Agentic AI for Healthcare with Snowflake Ventures Investment

Snowflake

Across every industry, organizations are adopting AI to drive new efficiencies and improve decision-making. The healthcare industry is complex and highly regulated. Compliance with regulatory statutes is mandatory, given the myriad rules around protected health information (PHI). The first step on the AI journey is building a robust data foundation, governance and security framework. Solving this challenge requires a new approach that can navigate these intricacies and unlock true efficiency.

The healthcare industry also expects an outcomes-driven approach to AI. That’s why we are thrilled to announce that Snowflake Ventures is investing in industry-AI disruptors like Penguin Ai to deliver innovations purpose-built for healthcare.

Penguin Ai has built a full-service, enterprise-grade AI platform to empower healthcare organizations to embrace AI with confidence and drive measurable outcomes across both the payer and provider ecosystem.

Founded in 2024 by the former chief data officer at Kaiser Permanente, United Healthcare and Optum, Penguin Ai delivers powerful, compliant AI solutions that reimagine complex healthcare workflows. The platform offers pre-trained AI models and sophisticated AI-based Digital Workers and Agents that automate high-cost, high-volume and data-intensive tasks. These include critical back-office processes like: prior authorization, medical coding, and HCC risk coding.

With this investment, Penguin Ai will bring its agentic AI solutions to the Snowflake Marketplace through a series of Snowflake Native Apps, empowering our customers to deploy fine-tuned healthcare LLMs and AI agents. This integration keeps sensitive data within the customer’s own Snowflake account and is designed to accelerate key industry workflows:

  • For payers: Streamline prior authorization, optimize claims processing, enhance HCC coding and risk analysis, appeals and grievances management, and payment integrity.
  • For providers: Automate medical coding, modernize document management and fax processing, streamline denials and appeals management, and accounts receivable (A/R) recovery.
  • For revenue cycle management: Enhance claims processing, enable AI-assisted billing and revenue capture, and automate denials and appeals.

At Snowflake, our mission is to help every enterprise achieve its full potential through data and AI. This investment brings Penguin Ai’s specialized applications into the Snowflake AI Data Cloud, giving our healthcare customers a powerful new way to accelerate their AI journey.

Get ready for Penguin Ai’s Snowflake Native App, launching soon on Snowflake Marketplace. To see how Snowflake is already empowering the industry, explore our solutions for healthcare and life sciences here.

Ebook

The Snowflake Life Sciences Playbook for AI, Apps and Data Collaboration

Explore 4 key industry use cases and over 10 leading AI, apps and data solutions.

Nea – From Algorithms to Atoms: Our Investment in CuspAI

NEa

It’s often said that the next decade is the age of atoms rather than bits. We believe advances in the latter will unlock breakthroughs in the former.

Looking at the evolution of intelligent systems, we can identify three distinct eras:

  1. First came the era of systems built on formal (mathematical) models and simulations, generating synthetic data and reasoning within well-defined, logic-driven, and largely deterministic representations of the world. Manual experiments by scientists persisted in this first era and were essential for validating and calibrating the models and simulations.
  2. Next was the era of systems that learned directly from large-scale experimental data, using statistical and probabilistic methods to capture patterns and make predictions from observed reality.
  3. The emerging era will blend these paradigms into agentic, closed-loop systems that can define goals, design and run simulations, select viable paths, commission physical experiments, interpret results, and adapt their strategies iteratively without human micromanagement. By tightly coupling in-silico design with real-world validation in rapid feedback cycles, these systems will accelerate computational discovery and extend intelligent problem-solving into complex domains of the physical world.

CuspAI is spearheading this emerging era in computational materials science, where novel materials can be generated, synthesized, tested and validated in months instead of the 10-20 year horizon the industry has learned to expect. Based in Cambridge, UK with teams across Amsterdam and Berlin, CuspAI has demonstrated exceptional vision and execution: building state-of-the-art models, partnering with industry leaders across different domains, and gathering a stellar team with more than 2 million citations collectively. The company’s innovative approach to computational materials science aligns perfectly with our investment philosophy in backing exceptional talent with a pragmatic approach to solving world-changing problems in high-impact industries. And that is why we are thrilled to have led their Series A financing round.

Why Materials Science?

Materials underpin nearly everything: the homes and infrastructure we build; energy generation, storage, and transmission; mobility and aerospace; computing, communications, and sensing; clean water and food systems; health care and medical devices; textiles and packaging; and national security. Advancements here ripple across the economy.

Historically, discovering a new material is slow and expensive – often a decade or more and tens to hundreds of millions of dollars from idea to deployment[1].

CuspAI’s platform uses inverse design – starting with target properties and working backward to propose candidates – then evaluates stability, performance, and manufacturability through fast feedback loops. In practice, that means high-fidelity simulations, learned surrogate models, degradation pathway modeling, and constraint-aware generation informed by experimental data.

The acceleration of materials discovery enables:

  • Addressing emerging challenges. e.g., filtration of PFAS (“forever chemicals”) from drinking water and industrial discharge.
  • Tackling persistent bottlenecks. e.g., safer solid-state electrolytes, longer-cycle batteries, low-loss power electronics, corrosion-resistant coatings, high-performance membranes for desalination and gas separation. 
  • Anticipate future demand. e.g., lightweight, high-temperature alloys for aerospace; rare-earth-lean magnets; thermal interface materials for data centers; recyclable or bio-derived polymers for packaging and apparel.

Why CuspAI?

We believe CuspAI has amassed a set of unique resources and strategies that are unparalleled in this space:

Professor Max Welling and Dr. Chad Edwards, co-founders of CuspAI

Stellar, interdisciplinary team: CuspAI is led by a highly reputable, interdisciplinary team that brings together deep expertise in ML, computational chemistry, and industrial process engineering — as exemplified by the co-founders.

  • Dr. Chad Edwards (Co-founder & CEO) was previously the Commercial Co-Founder of Cambridge Quantum Computing (CQC). He later served as VP of Strategic Partnerships and Global Head of Strategy at Quantinuum following CQC’s merger with Honeywell.
  • Professor Max Welling (Co-founder & CTO) is a Professor at University of Amsterdam, and previously VP Technology at Qualcomm AI Research and Distinguished Scientist at Microsoft Research. He is considered a pioneer in AI’s application to science, variational inference, probabilistic deep learning, and geometric deep learning.

Focus on large scale, curated data collection: CuspAI recognizes that high-quality, large-scale data is foundational to building state-of-the-art models. The team has made early and deliberate investments in building proprietary datasets at scale, including MOFs, to enable models that are both high-performing and generalizable across material classes. In addition, CuspAI runs tight integrations with downstream experimental data pipelines for simulation, synthesis, and testing workflows. This is also complemented by academic and scientific literature through licensing agreements.

Partnering with industry leaders across various domains: CuspAI partners directly with commercially successful businesses and industry leaders to drive impact at scale – aligning closely with partners’ priorities, and building deep collaborations across sectors like energy, climate, automotive, and semiconductors. In addition, CuspAI has assembled a distinguished advisory board that includes Nobel laureate Geoff Hinton (Turing Award laureate, deep learning pioneer), Yann LeCun (Turing Award laureate, Chief AI Scientist at Meta), Lord John Browne (former CEO of BP), Martin van den Brink (former President & CTO of ASML), Verity Harding (former Global Head of Policy at DeepMind), and Prof. Kristin Person (a leading figure in materials science).

Achieving SOTA model performance: CuspAI’s core model stack is fully proprietary, designed to cover end-to-end materials discovery lifecycle from micro-scale design (molecular and atomic levels) to macro-level deployment (process and manufacturability). The CuspAI platform includes a suite of generative models like MOFGEN, a state-of-the-art autoregressive transformer for metal-organic frameworks (MOFs) that achieves a VUN (valid, unique, novel) rate of 49%, which outperforms by a large margin models from Microsoft (10%) and Meta (16%)[2]. Unlike simpler inorganic generators, MOFGEN produces highly complex, synthesizable structures validated against strict physical and chemical constraints and tested against experimental data generated from industry partners.

The Future of Materials

We believe that CuspAI will play a crucial role in shaping the future of materials discovery for generations to come, and will touch many aspects of our physical world from the chips powering our machines to ensuring the sustainability of our environment.

With our investment, CuspAI will be able to accelerate its research and development efforts, expand its market reach, and further solidify its position as a leader in the domain. We are thrilled to partner with Chad, Max, and the entire CuspAI team. Their vision and ambition have the potential to reshape the world, and we can’t wait to be part of that journey.

by Lila Tretikov, Philip Chopin, Andrew Schoen and Aya Somai

TERN Group Raises $24M to Tackle the Global Healthcare Workforce Shortage with AI

RTP Global

Healthcare systems around the world are under immense strain. Demand for care is rising, but workforce capacity isn’t keeping pace. The World Health Organisation predicts that the global healthcare industry will face a shortfall of 18 million healthcare workers by 2030.

Talented and skilled professionals can be deployed to fill these gaps globally, but the systems for healthcare providers to source and relocate global talent are broken. TERN Group offers a solution.

Tackling healthcare problems at scale

After building category-defining businesses across Europe and India, including multinational online used car marketplace Cars24 and PropTech platform IMMO, Avinav Nigam teamed up with Krishna Ramkumar, whose background spans BCG, Nexus Venture Partners and social impact ventures. They launched TERN Group in 2023, inspired by first-hand experiences of the complexities of relocation and migration, as well as the acute skilled talent shortage across the UK, Europe and the Gulf.

Together, they have built the world’s first AI Clinical Workforce Platform. It’s designed for healthcare providers to connect with the global talent they require, with support for sourcing, credentialing, training, and onboarding. TERN Group’s platform vastly improves on the slow and bureaucratic processes typical of international recruitment with a combination of AI-driven workflows and human-led support for training, relocation and settlement.

Importantly, the platform delivers a far more positive experience for both sides of the hiring contract. Healthcare providers access talent fast and more predictably, while talented professionals begin their global careers with dignity and confidence, free of unethical recruitment practices.

Today, London-headquartered TERN Group employs a team of 133 people worldwide across core markets of Germany, UK, UAE, KSA, Japan and the USA. It’s trusted by over 100 healthcare clients and is supporting a global talent pool of 650,000+ professionals across 13 countries.

The future of healthcare talent mobility

Having expanded from one to six core markets this past year, TERN Group is now focused on strengthening its foothold across these markets in addition to accelerating the development of its AI Clinical Workforce platform and ramping up investment in international talent preparation.

We’re delighted to be partnering with Avinav and team through this next phase of growth as an investor in TERN Group’s $24M Series A funding round. You can read more about that raise in Entrepreneur.

Commenting on the raise, Galina Chifina, CEO of RTP Global, said: “At RTP Global, we love backing founders who take on big challenges with heart. Avinav and Krishna are just those founders – solving problems they’ve lived and felt. With TERN, they’re reimagining global talent mobility in a way that’s ethical, scalable, and deeply human, turning it into a powerful, tech-driven solution. We can’t wait to see how TERN will continue to change lives across borders, and we’re delighted to back them on this journey.”

Skilled worker shortages are a truly global challenge. TERN is rising to that challenge with an appropriately global solution that combines AI-driven agility with human support for an end-to-end solution to transform skilled talent mobility.

With AI at its core and scale on the horizon, TERN Group is redefining how healthcare talent moves across the world.

CoreWeave Launches Ventures Group to Invest in Future of AI

CoreWeave Ventures

LIVINGSTON, N.J. – September 9, 2025 – CoreWeave (Nasdaq: CRWV), the AI Hyperscaler™, today announced the launch of CoreWeave Ventures, a new initiative committed to backing founders and companies developing the platforms and technologies shaping the AI ecosystem and the next frontier of computing.

As AI adoption expands across industries, demand for purpose-built infrastructure, tools, and applications continues to grow. By providing investment resources, technical expertise, and compute, CoreWeave Ventures enables founders to bring new ideas to market faster.

“We started CoreWeave with the conviction that AI’s true promise required a cloud platform built from the ground up to optimize for AI specific workloads. It took audacity, humility, and the support of other believers who helped us create the cloud platform of choice for many of the largest AI labs and enterprises” said Brannin McBee, Co-founder and Chief Development Officer, CoreWeave. “Our aim with CoreWeave Ventures is to give other audacious, like-minded founders the support they need to drive technical advancements and bring to market the next class of innovation.”

CoreWeave Ventures supports founders in driving the development of their platforms by providing:

  • Variety of capital investment models to help companies scale.
  • Accelerated access to the CoreWeave  cloud platform purpose-built for AI.
  • Testing environments across production-grade performance clusters to fast track new real-world use cases in AI.
  • Insights on product and go-to-market strategies shaped by CoreWeave’s relationships with hundreds of enterprises and AI-first organizations.
  • Opportunities for deep technical alignment through technology partnerships and integrations.

“Working with CoreWeave has given us the freedom to think bigger and move faster,” said Naeem Talukdar, co-founder and Chief Executive Officer, Moonvalley. “They understand the challenges of scaling breakthrough technologies and have backed us with the kind of support that lets us focus on innovation. We’re grateful to have a partner that invests in both our company and the future we’re trying to create.”

CoreWeave Ventures supports founders with the resources to create impact from day one, ranging from direct capital investment and compute-for-equity transactions to technical collaboration and go-to-market opportunities. CoreWeave Ventures is already working with a diverse group of innovators, from foundational model developers building novel large language models to pioneers in vertical AI applications and infrastructure.

To learn more about CoreWeave Ventures, visit:  www.coreweave.com/ventures or email ventures@coreweave.com.

About CoreWeave

CoreWeave, the AI Hyperscaler™, delivers a cloud platform of cutting-edge software powering the next wave of AI. The company’s technology provides enterprises and leading AI labs with cloud solutions for accelerated computing. Since 2017, CoreWeave has operated a growing footprint of data centers across the US and Europe. CoreWeave was ranked as one of the TIME100 most influential companies and featured on Forbes Cloud 100 ranking in 2024. Learn more at www.coreweave.com.

SurveyMonkey launches new AI Analysis Suite and design tools, unlocking clear insights and beautiful surveys without the complicated process

Stg Partners

SurveyMonkey today announced its latest SurveyMonkey AI innovations, including a new AI Analysis Suite and supercharged survey creation tools. The new features are designed to help users ask better questions, make smarter decisions, and move faster.

“SurveyMonkey has always been in the business of capturing real human sentiment and turning it into action,” said Meera Vaidyanathan, Chief Product Officer at SurveyMonkey. “AI now lets us do this faster and smarter—automating the legwork, surfacing insights that were previously hidden, and helping our customers act with greater confidence. With 25 years of history and more than 100 billion questions answered, we’re uniquely positioned to deliver trusted AI that makes feedback not just easier to gather, but far more powerful.”

Mistral: AI for tomorrow’s enterprise

Index Ventures

Mistral cofounders: Timothée Lacroix, Arthur Mensch, Guillaume Lample

INDEX PERSPECTIVE

By Julia Andre

Strong relationships create their own serendipity. A few years ago, my colleague Jan Hammer and I were visiting the Paris HQ of Alan, the digital health insurance platform in which Index was an early investor. Alan’s CEO and co-founder, Jean-Charles Samuelian-Werve, mentioned that he was incubating an open-source AI startup called Mistral a couple of floors below. After meeting his co-founder Arthur Mensch, we knew we had to be part of the journey.

Index invests in people as much as we invest in companies – which is why, after cutting that first seed check for Mistral, we’re thrilled to be continuing to support Arthur and the team in their latest funding round. At heart, Arthur is the kind of deeply technical engineer who could easily be building Mistral’s core models himself. Yet he’s shown himself to be talented at communicating Mistral’s bigger vision to customers, investors and policymakers. As a founder, it’s rare and incredibly powerful to be able to flip so fluidly between the close-up and the birds-eye view of your company.

That macro perspective is crucial as Mistral rides – and drives – a transformational wave in how businesses use AI. It’s no longer an experimental, ‘nice-to-have’ technology that employees are using ad-hoc; instead, we’re moving towards a world in which every major company will need to have a customized intelligence at its core. ASML’s decision to strategically partner with Mistral is a reflection of this. Mistral has shown impressive execution in building custom decentralized frontier AI solutions to solve the most complex engineering and industrial problems. More than simply selling cutting-edge models and LLMs, Mistral is en route to becoming the implementation partner of choice for enterprise – a one-stop shop for organizations putting AI to work at scale.

Mistral is the unquestioned AI leader being built out of Europe. Yet what excites us most is that it’s still early days. The enterprise AI market is just beginning to take shape, and Mistral’s success sets it up to be one of the big winners over the long term. We’re delighted to support them as they build the crucial AI infrastructure of tomorrow.

THE DETAILS

Mistral AI raises €1.7bn to accelerate technological progress with AI

Mistral announced a Series C funding round of €1.7bn at a €11.7bn post-money valuation. This investment fuels the company’s scientific research to keep pushing the frontier of AI to tackle the most critical and sophisticated technological challenges faced by strategic industries.

The Series C funding round is led by leading semiconductor equipment manufacturer, ASML Holding NV (ASML).

“ASML is proud to enter a strategic partnership with Mistral AI, and to be lead investor in this funding round. The collaboration between Mistral AI and ASML aims to generate clear benefits for ASML customers through innovative products and solutions enabled by AI, and will offer potential for joint research to address future opportunities.” said ASML CEO Christophe Fouquet.

For the last two years, Mistral has advanced AI through cutting-edge research and strategic partnerships with corporate and industrial champions. They will continue to develop custom decentralized frontier AI solutions that solve the most complex engineering and industrial problems. It powers enterprises, public sectors, and industries through state-of-the-art models, tailored solutions, and high-performance compute infrastructure.

“This investment brings together two technology leaders operating in the same value chain. We have the ambition to help ASML and its numerous partners solve current and future engineering challenges through AI, and ultimately to advance the full semiconductor and AI value chain”, said Mistral AI CEO Arthur Mensch.

SurveyMonkey launches new AI Analysis Suite and design tools, unlocking clear insights and beautiful surveys without the complicated process

Stg Partners

SurveyMonkey today announced its latest SurveyMonkey AI innovations, including a new AI Analysis Suite and supercharged survey creation tools. The new features are designed to help users ask better questions, make smarter decisions, and move faster.

“SurveyMonkey has always been in the business of capturing real human sentiment and turning it into action,” said Meera Vaidyanathan, Chief Product Officer at SurveyMonkey. “AI now lets us do this faster and smarter—automating the legwork, surfacing insights that were previously hidden, and helping our customers act with greater confidence. With 25 years of history and more than 100 billion questions answered, we’re uniquely positioned to deliver trusted AI that makes feedback not just easier to gather, but far more powerful.”

The Missing Emotional Layer in AI: Our Investment in Nuance Labs

Lightspeed

Nuance Labs Co-Founders Fangchang Ma and Edward Zhang

We’ve all experienced the uncanny valley: the slight discomfort when watching an AI avatar speak, the sense that something fundamental is missing despite impressive technical capabilities. Today’s AI can reason brilliantly and generate human-like text, but when it comes to emotional intelligence, AI remains surprisingly tone-deaf.

That’s where Nuance Labs comes in. We at Lightspeed are excited to invest in their seed round alongside Accel as they build what we believe will become a foundational layer for emotional intelligence in AI.

As IQ becomes commoditized through increasingly capable language models, emotional quotient (EQ) emerges as the critical differentiator. Yet we believe current AI systems fundamentally miss this dimension. AI avatars feel robotic, not because of pixel quality, but because they lack the subtle emotional expressiveness that makes human faces compelling, and they are far from real-time responsiveness.

Nuance’s breakthrough insight mirrors that of large language models: just as LLMs learned to understand meaning by predicting the next word, AI can understand emotions by learning to predict human emotions and behavior.

Nuance Labs is building a unified foundation model for real-time generation and understanding of realistic human expression across multiple simultaneous modalities, including text, speech, and video. This unlocks new categories of AI interaction:

  • Real-time emotional generation: Lifelike avatars that don’t just speak words but convey appropriate emotional responses through coordinated facial expressions, vocal inflection, and body language. Imagine AI therapists that pause thoughtfully, offer encouraging expressions, and adapt their demeanor to your emotional state, all in real-time.
  • Real-time emotion understanding: AI systems that can read subtle emotional cues as they happen, enabling applications like live coaching systems that detect when you’re losing confidence during a presentation, or interview AI that understands not just what candidates say but how they say it.

The team brings exceptional depth: Fangchang Ma and Edward Zhang previously built research teams at Apple, contributing to products like Vision Pro’s Digital Persona system. Their combined expertise in computer graphics, robotics, and machine learning, along with thousands of academic citations, strongly positions them to solve this technically complex challenge.

We’re entering an era where AI interactions will be measured not just by accuracy or speed, but by emotional authenticity. Any interface where humans interact with AI, from customer service and education to entertainment and healthcare, will benefit from emotional intelligence. We believe Nuance Labs is building the infrastructure that will power this next generation of AI experiences.

The uncanny valley stands as a barrier to natural human-AI interaction. Nuance Labs is building a bridge that will enable an entire ecosystem of emotionally intelligent AI applications. We’re thrilled to support their mission to make AI interactions as natural and emotionally rich as human conversation itself.

Excited to bring emotional intelligence to artificial intelligence? Nuance is hiring.

 

The content here should not be viewed as investment advice, nor does it constitute an offer to sell, or a solicitation of an offer to buy, any securities. Certain statements herein are the opinions and beliefs of Lightspeed; other market participants could take different views.

Nnamdi Iregbulem

Nnamdi Iregbulem

Guru Chahal

Guru Chahal

Motion raises $60M at a $550M valuation to redefine the next era of work

Motion raises $60M at a $550M valuation to redefine the next era of work

Four years ago, we met Harry Qi and his co-founders over coffee in San Francisco. The product itself was still raw, but the team’s conviction was undeniable. They weren’t just chasing a clever feature; their goal was to redefine how millions of people work.

That belief led us to back Motion’s Series A in 2020. Four years later, we’ve doubled down with super-prorata participation in every round, including Motion’s newly announced $60M raise at a $550M valuation across Series B, C, and C2.

From niche tool to category-defining agentic suite

Like many startups, Motion started with a niche focus: An AI-powered calendar and task manager that was a smart wedge into a noisy space. The founders quickly realized they were onto something bigger. Managing tasks solved part of the problem, but what if the platform could take the next step and execute them?

They began expanding Motion into what it is today: a complete agent-native work suite. Beyond calendars, Motion powers project management, docs, sheets, tasks, knowledge management, and business intelligence, designed for seamless human and AI collaboration.

The team’s latest innovation is ‘AI Employees.’ Think of them as out-of-the-box digital teammates that don’t just track work, but complete it. They can draft proposals, update project plans, and respond to client requests, all within the same platform their human teammates use.

 

We always asked ourselves: “Why should AI tasks live outside the systems where human tasks already run?” By unifying them, we unlock 100 times the value and give SMBs the same leverage that Fortune 500s get from expensive custom AI builds.
Harry Qi
Co-Founder & CEO, Motion

A playbook any founder can learn from

Watching Motion scale has been a masterclass in startup building. For founders, these are the lessons worth underlining:

  • Velocity wins. Motion ships with a speed that’s rare even in Silicon Valley. Features move from whiteboard to customer hands in days, not quarters.
  • Reinvent to expand. Calendaring was never the endgame. The team continuously reinvented the product until they unlocked a path to building the entire work suite of the agentic era, perhaps what Microsoft Office would look like if it were invented today.
  • Stay close to your customer. While big enterprises experiment with armies of AI engineers, Motion stayed focused on SMBs, which are the backbone of the economy. Over 80% of new ARR comes from this segment.

The results speak for themselves: 100,000+ paying customers, ARR tripling year-over-year, and $10M in new ARR from ‘AI Employees’ in just four months.

Built for everyday businesses

AI headlines often center on Big Tech or bleeding-edge AI labs, but Motion’s north star is different: the everyday businesses that keep America running.

 

‎Think of a design agency in Tennessee, a small IT firm in Alabama, or a marketing shop in Texas. These aren’t companies with dedicated AI teams; they’re lean teams that answer their own phones, juggle client deadlines, and need a system that simply works.That’s what Motion delivers: a platform where human and AI employees sit side by side, running the business together.

The impact is tangible:

  • An IT services CEO credits Motion’s AI project manager with cutting delivery time by 30%.
  • Marketing agencies report saving hours each week thanks to AI-powered executive assistant agents.
  • Customers say Motion is the first platform where “AI feels truly built-in, not bolted on.”

For their customers, Motion is the core operating system for how they work.

 

In just a few years, a single human will manage hundreds of AI Employees completing thousands of tasks inside the Motion platform. Our vision has always been to help everyday businesses grow by letting AI handle the busywork, so humans can focus on what really matters.
Harry Qi
Co-Founder & CEO, Motion

Why we’re doubling down on this team

We’ve partnered with Motion through its biggest wins and its toughest challenges, and what stands out is how the team shows up in both moments. Four years in, their co-founders are still working shoulder-to-shoulder. They’ve since welcomed seasoned leaders like Luis Carrasco (ex-Microsoft Teams), Antonio Garcia (ex-Salesforce), and Ashutosh Desai (founder of Make School and former Visiting Partner at Y Combinator) to the team, blending startup urgency with enterprise-scale experience. The culture they’ve built is ambitious yet humble, fast, and thoughtful.

 

Motion founders: Ethan Yu, Harry Qi, Chander Ramesh, and Omid Rooholfada.

This is a team built to win big. Here’s how they describe their recent momentum:

  • Growth: B2B ARR growing 3x year-over-year and scaling 20% month-over-month.
  • Product-market fit: Over 80% of ARR comes from SMBs and mid-market customers (businesses that need ready-to-use solutions, not armies of consultants).

We’ve continued to lean in because Motion is exactly the kind of team and market opportunity we’re excited to back. At SignalFire, we couldn’t be prouder to have been there since the beginning, and to keep backing Harry and the team at every step forward.

Join the mission – an invitation to builders

Motion is now a 65-person team with the drive of a scrappy startup and the ambition of a category-definer. With this new funding, they’re hiring across engineering, product, and AI research to expand the agentic suite and push the frontier of what’s possible.

For founders, Motion’s story is a reminder to start narrow, move fast, listen obsessively, and never stop reinventing. For builders, it’s an opportunity to help shape the next great work suite for the AI era, which empowers everyday businesses to thrive.

Explore open roles here.

Read TechCrunch’s coverage of the announcement here.

Koah raises $5M to bring ads into AI apps

Forerunner

How can startups and developers actually monetize their AI products? A startup called Koah, which recently raised $5 million in seed funding, is betting that ads will be a big part of the answer.

If you spend any time online, there’s a good chance you’ve seen plenty of ugly, AI-generated ads — but few to none when interacting with AI chatbots. Koah co-founder and CEO Nic Baird argued that will inevitably change.

“Once these things get outside San Francisco, there’s only one way to make [them profitable] on a global scale,” Baird told TechCrunch over Zoom. “It’s happened time and time again.”

To be clear, Koah isn’t trying to introduce advertising to ChatGPT. (That’s probably something OpenAI will do for itself one day.) Instead, it’s focused on the “long tail” of apps that are built on top of the big models, including apps with a user base outside the United States.

Baird suggested that when consumer AI products were first becoming popular, it made sense for them to focus on “wealthier, prosumer” users and to monetize those users by converting some of them into paid subscriptions.

But now someone could build an AI app that reaches millions of users in Latin America, and those users are “not paying 20 dollars a month,” Baird said. So the developer could struggle to bring in subscription revenue, but “they have the same inference costs as everyone else.”

A sample Koah ad for acne wash
Image Credits:Koah

Baird suggested that by successfully figuring out how to make advertising work in AI chats, Koah could actually unlock more potential for “vibe coded” apps that might otherwise be “too expensive to operate at scale” unless their creators raise VC funding.

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In fact, Koah is already serving ads in apps like AI assistant Luzia, parenting app Heal, student research tool Liner, and creative platform DeepAI. Its advertisers include UpWork, General Medicine, and Skillshare.

These ads are marked as sponsored content, and they’re supposed to appear at relevant moments in your chats. For example, if you’re asking for advice about startup business strategies, the app could show you an ad from UpWork offering to connect you with freelancers who could work with your company.

When Koah talks to publishers, Baird said many of them believe that ads simply don’t work in AI chats, while others have found limited success with AI offerings from older adtech companies like AdMob and AppLovin.

But Baird said Koah is 4x to 5x more effective, delivering clickthrough rates of 7.5%, and with early partners earning $10,000 in their first 30 days on the platform. He added that Koah achieves all that while having less of a detrimental effect on user engagement — though his ultimate goal is for Koah ads to feel relevant enough that they actually improve engagement.

Image Credits:Koah

Koah’s seed round was led by Forerunner, with participation from South Park Commons and AppLovin co-founder Andrew Karam.

Forerunner partner Nicole Johnson echoed many of Baird’s points when discussing the investment over email. She said that when it comes to AI, monetization is “the elephant in the room amongst builders and investors.” And while the “going standard for monetizing consumer AI services is subscription,” focusing exclusively on subscriptions can “quickly lead to fatigue and churn.”

“Multiple revenue models in Consumer AI are inevitable, and if the past decades of internet services are any indicator, ads will play a major role,” Johnson said. In her view, Koah is “building the essential monetization layer for consumer AI services.”

As for where AI chats fall in the larger advertising ecosystem, Baird and his team have found they represent the middle of the purchase funnel — somewhere between the awareness raising of an Instagram ad and the actual purchase that might be driven by ads in Google search.

“People are not transacting on AI — they’re just not,” Baird said. They might ask a chatbot for recommendations or product details, but then “they’re going to Google to buy.” So part of the challenge for Koah is figuring out the best ways to capture a user’s “commercial intent.”

“It’s not interesting to me to try to figure out, ‘How do we show a display ad in AI?” Baird said. Instead, he wants to understand, “What is the user looking for and how do we give that to them?”

Anthony Ha is TechCrunch’s weekend editor. Previously, he worked as a tech reporter at Adweek, a senior editor at VentureBeat, a local government reporter at the Hollister Free Lance, and vice president of content at a VC firm. He lives in New York City.