--- url: 'https://qubit.capital/blog/us-series-a-weekly-funding-roundup-week-1-june-2026' title: 'US Series A Weekly Funding Roundup (May 30-Jun 6, 2026): $124.0M Raised Across 4 Deals' author: name: Sahil Agrawal url: 'https://qubit.capital/blog/author/sahil' date: '2026-06-06T03:44:27+05:30' modified: '2026-06-05T11:29:18+05:30' type: post summary: 'Four US startups raised $124M in Series A funding this week. Mecka AI, Sekai, Waypoint Bio, and Novellia drew checks across AI, robotics, and healthtech.' categories: - Weekly Funding Roundup image: 'https://qubit.capital/wp-content/uploads/2026/06/featured-us-series-a-67439.webp' published: true --- # US Series A Weekly Funding Roundup (May 30-Jun 6, 2026): $124.0M Raised Across 4 Deals Four US startups closed Series A rounds in the week of May 29 to June 5, pulling in $124 million between them. AI and healthtech split the haul almost evenly. Two AI companies, Mecka AI and Sekai, took $86 million of the total, while a cell-therapy startup and a patient-data platform raised the rest. Mecka AI’s $60 million round accounted for nearly half the week’s money on its own. The mix says something about where early checks are landing right now. Robots that learn from human motion and platforms that hand medical records back to patients both attracted name-brand funds. Still, these first institutional rounds looked small next to what raised later in the cycle. Three US Series B and later deals collected $892.5 million over the same stretch, a reminder that growth-stage money moves in far bigger blocks than Series A capital. The four founders below are betting on data nobody else has yet. Table of Contents - [1. Mecka AI Raises $60M For Robot Training Data](#1-mecka-ai-raises-$60m-for-robot-training-data) [Deal Overview](#deal-overview) - [Investor Profile](#investor-profile) - [Company and Leadership](#company-and-leadership) - [Problem and Opportunity](#problem-and-opportunity) - [Product and Technology](#product-and-technology) - [Use of Proceeds and Vision](#use-of-proceeds-and-vision) - [Market Context](#market-context) - [2. Sekai Raises $26M For Consumer AI App Building](#2-sekai-raises-$26m-for-consumer-ai-app-building) [Deal Overview](#deal-overview-1) - [Investor Profile](#investor-profile-1) - [Company and Leadership](#company-and-leadership-1) - [Problem and Opportunity](#problem-and-opportunity-1) - [Product and Technology](#product-and-technology-1) - [Use of Proceeds and Vision](#use-of-proceeds-and-vision-1) - [Market Context](#market-context-1) - [3. Waypoint Bio Raises $20M For AI-Designed Cell Therapies](#3-waypoint-bio-raises-$20m-for-ai-designed-cell-therapies) [Deal Overview](#deal-overview-2) - [Investor Profile](#investor-profile-2) - [Company and Leadership](#company-and-leadership-2) - [Problem and Opportunity](#problem-and-opportunity-2) - [Product and Technology](#product-and-technology-2) - [Use of Proceeds and Vision](#use-of-proceeds-and-vision-2) - [Market Context](#market-context-2) - [4. Novellia Raises $18M For Patient-Controlled Health Data](#4-novellia-raises-$18m-for-patient-controlled-health-data) [Deal Overview](#deal-overview-3) - [Investor Profile](#investor-profile-3) - [Company and Leadership](#company-and-leadership-3) - [Problem and Opportunity](#problem-and-opportunity-3) - [Product and Technology](#product-and-technology-3) - [Use of Proceeds and Vision](#use-of-proceeds-and-vision-3) - [Market Context](#market-context-3) - [Lessons For Founders](#lessons-for-founders) ## 1. Mecka AI Raises $60M For Robot Training Data ### Deal Overview - **Stage:** Series A - **Sector:** AI, robotics data infrastructure - **Geography:** New York City and Toronto - **Round size:** $60 million, assembled as a $25M initial round in November 2025 plus a roughly $35M extension in spring 2026 - **Total raised:** about $68 million since the company formed ### Investor Profile Framework Ventures, Menlo Ventures, SV Angel, and Kindred Ventures backed the round. Menlo and SV Angel bring decades of early-stage track record, and Framework has pushed into AI infrastructure bets. Their presence signals conviction that the data layer for robotics, not the robots themselves, is where the next returns sit. ### Company and Leadership [Mecka AI](https://www.mecka.ai/) was founded in 2025 by CEO Josh Gao with co-founders Mogen Cheng, Jason Chong, and Duy Nguyen. None came from AI labs. Gao and Cheng sold a restaurant payments startup, Chong sold a company to Coinbase, and Nguyen built a sneaker-resale business. Most of its 40 to 45 staff sit in Toronto. ### Problem and Opportunity Robots can’t learn dexterous tasks without examples, and the usual way to gather those examples, teleoperation rigs, costs too much to scale. That data gap has become the main bottleneck in physical AI. Mecka thinks it can fill it cheaply. ### Product and Technology Mecka runs a human-motion data engine. It captures hand gestures, walking gaits, and full-body movement using custom wearable sensors paired with iPhones running its own capture software. It also collects first-person video from kitchens, chemistry labs, metal shops, and homes. That raw capture becomes training corpora for vision-language-action and world models. The moat is the dataset itself. Collecting real-world demonstrations at low cost, across many physical settings, gives Mecka behavioral data that rivals would struggle to copy. ### Use of Proceeds and Vision The money goes toward scaling data collection and helping companies deploy robots in the field. Gao argues useful robots can ship today, not in some distant future. Mecka wants to be the data-and-deployment layer rather than a robot maker, and reportedly projects a $100 million annual run rate from existing contracts. ### Market Context The deal lands in the middle of an intense 2026 race in humanoid robotics, where training data is the scarce input. Foundation-model labs like Physical Intelligence and Skild AI sell generalist robot brains, while Figure AI and Tesla train in-house. Investment in world models reportedly jumped from about 1.3 billion euros in 2024 to 6.5 billion in 2025. Mecka stays hardware-agnostic and sells the data instead. ## 2. Sekai Raises $26M For Consumer AI App Building ### Deal Overview - **Stage:** Series A (plus seed, announced together) - **Sector:** AI, consumer software - **Geography:** San Francisco Bay Area - **Round size:** $26 million combined, including a $20 million Series A - **Traction:** more than 15 million mini-apps created, roughly 200,000 added daily ### Investor Profile [Sekai](https://sekaiapp.com) drew Khosla Ventures, Connect Ventures, Mayfield, a16z speedrun, and 645 Ventures. Keith Rabois at Khosla and Nicole Quinn at Connect co-led the Series A, with Navin Chaddha at Mayfield leading the seed. That roster of consumer and contrarian investors fits a bet on a new consumer category rather than a developer tool. ### Company and Leadership Founded in 2024, Sekai is serial founder Lucky Zhang’s fourth company. His first was acquired by Apple, his second became the largest short-video platform in Latin America before TikTok bought it, and his third is Vietnam’s largest music streaming service. He has built and sold consumer products at scale before. ### Problem and Opportunity Making software still requires code, which locks out almost everyone. Zhang’s wager is that creation should be as easy as describing an idea. If that holds, the audience isn’t developers, it’s everyone who uses a phone. ### Product and Technology Users describe what they want in plain language, and Sekai turns it into a playable, shareable mini-app: games, memes, quizzes, polls, fan tools. Creations work immediately, and people can remix each other’s apps. It runs on web, iOS, and Android under the tagline Create, Play, Remix. The defensibility comes from the remix graph. As users fork and modify each other’s apps, Sekai accumulates data on what gets made and what spreads. The company asserts this network effect, though it hasn’t been independently verified. ### Use of Proceeds and Vision The capital funds engineering and product hiring plus creator partnerships, including a deal with Creative Artists Agency. Zhang frames Sekai as the home for the vibe-coding generation, a place where non-technical people make interactive content. ### Market Context Sekai sits in the consumer AI app-builder market alongside Replit, Lovable, Bolt, and v0. Those tools lean toward developers and single-app productivity. Sekai goes the other way, targeting consumers with a social feed of short, remixable apps. ## 3. Waypoint Bio Raises $20M For AI-Designed Cell Therapies ### Deal Overview - **Stage:** Series A - **Sector:** Healthtech, AI-native biotech - **Geography:** New York City - **Round size:** $20 million, announced June 1, 2026 - **Prior funding:** a $14.5 million seed in 2024 ### Investor Profile Amplify Partners led, and Elliot Hershberg joined the board. General Catalyst, Lux Capital, Time BioVentures, Mitsui Global Investments, and returning backer Hummingbird Ventures took part. The mix of deep-tech and bio investors reflects a company that lives between AI and the wet lab. ### Company and Leadership [Waypoint Bio](https://www.waypointbio.com/) launched in 2024, founded by CEO Xinchen Wang and CSO David Phizicky, both MIT alumni with wet-lab and computational backgrounds. CTO Patrick Kaifosh co-founded CTRL-Labs before Meta acquired it. Kristen Hege, formerly an early-development lead at Bristol-Myers Squibb, sits on the scientific board. ### Problem and Opportunity CAR-T cured many blood cancers but has mostly failed against solid tumors, which make up the majority of cancers. The reasons are antigen heterogeneity, poor T-cell infiltration, and a hostile tumor environment that exhausts the cells. Waypoint built its platform to attack exactly that. ### Product and Technology The platform fuses three pieces: generative AI to design candidates, spatial biology and computer vision to watch how they behave inside tumors at single-cell resolution, and pooled in vivo screening that tests thousands of designs head to head. Its lead program, WAY-103, is an in vivo CAR-T paired with a proprietary lentiviral vector targeting gastric and pancreatic tumors, reporting more than 15-fold greater potency than clinical benchmarks in animal models. Wang frames the edge as validation, not prediction. The rich spatial readouts come from designs tested inside living tumors, data standard lab assays can’t produce, which matters because public solid-tumor CAR-T datasets are small. ### Use of Proceeds and Vision The round pushes WAY-103 into an investigator-initiated clinical trial in China beginning in late 2026. It also expands the AI and spatial-biology platform and advances WAY-200, a colorectal-cancer program. The strategy favors fast first-in-human studies over years of preclinical tuning. ### Market Context Companies like Poseida, Tessa Therapeutics, and UTC Therapeutics work on novel CAR constructs, while a newer cohort applies AI and spatial biology. Data scarcity is the field’s constraint, which is why Waypoint’s proprietary in vivo screening data reads as a real differentiator. Its China-first clinical path sets it further apart from ex vivo incumbents. ## 4. Novellia Raises $18M For Patient-Controlled Health Data ### Deal Overview - **Stage:** Series A - **Sector:** Healthtech, real-world data - **Geography:** New York City - **Round size:** $18 million, bringing total funding to roughly $28 million - **Customers:** several of the top 10 pharmaceutical companies ### Investor Profile Spark Capital, Khosla Ventures, Acrew Capital, Bling Capital, and TMV backed the round. The group spans consumer and health investors, fitting a product that is both a free patient app and a data business selling to pharma. ### Company and Leadership [Novellia](https://novellia.com) was founded in 2023 by CEO Shashi Shankar, a former Genentech and Roche executive, CTO Elliot Katz, an early ZocDoc engineer, and CMO Dr. Abe Abraham, a Johns Hopkins-trained physician and former Genentech drug developer. Shankar has said the idea came from watching his family struggle to coordinate care during his grandfather’s fatal cancer. ### Problem and Opportunity A patient’s records sit scattered across hospitals, clinics, and labs, and no single party holds the full story. Pharma buys fragments from brokers and stitches together an incomplete picture. Novellia thinks the patient is the missing source of truth. ### Product and Technology Its free app pulls up to 20 years of medical history from disparate US health systems into one record in under 30 seconds. Proprietary NLP models extract structured signals from physician notes, lab narratives, and diagnostic reports. Patients decide whether to share de-identified data, which Novellia harmonizes into research-ready datasets it sells to drugmakers. Because the data comes directly from consenting patients rather than brokers, the records run more complete and longitudinal than claims-only or EHR-only sets. The company cites research showing nearly 70% of patients share data when given control and transparency. ### Use of Proceeds and Vision The capital scales the consumer app and the consented data network behind it. Novellia says it has signed seven-figure, multiyear contracts with some of the world’s largest drugmakers since the round closed. It calls its approach digitomics, a digital complement to multiomics. ### Market Context Real-world data has become central to drug development, yet EHR, claims, and device data stay siloed in a market Novellia pegs at about $50 billion a year. PicnicHealth, Komodo Health, Datavant, and Truveta all compete here. Novellia’s wedge is sourcing data directly from patients who opt in, betting that fully consented records are both higher quality and harder to replicate. ## Lessons For Founders - Sell the data layer, not the end product. Mecka chose to supply training data for robots rather than build robots, and Novellia sells consented patient data rather than a clinic. Picks-and-shovels plays can capture a boom without carrying its hardest engineering risk. - A proprietary dataset that’s expensive to gather is the strongest moat in AI right now. Three of these four companies pitched data nobody else holds, and investors paid for it. - Operator track record moves rounds. Lucky Zhang’s prior exits and Shashi Shankar’s pharma background gave investors a reason to write checks before the products had proven out. - Validation beats prediction in regulated fields. Waypoint won its round by testing designs inside real tumors, not by claiming its AI could guess the answer. Rigorous proof de-risks the bet. - You don’t need to be the biggest raise to be the smartest. The week’s late-stage deals dwarfed these four, but a focused $18 million round with named pharma contracts can matter more than a flashy headline number.