# Endra and Sekai Lead New Deals as Physical-Economy and Workflow AI Gain Momentum

*By VC Tech Radar • June 2, 2026*

Endra’s Series A and Sekai’s $26M round were the clearest financing signals, while YC launches showed continued momentum in workflow-native AI across healthcare, robotics, developer tooling, and operations. The broader backdrop remains aggressive AI growth, rising capex, and new investable layers in agent safety and physical-economy software.

## Funding & Deals

- **Endra — $50M Series A led by a16z.** The round brings total funding to $74M in 12 months. Endra automates mechanical, electrical, and plumbing design for data centers, hospitals, and buildings: engineers set rules for systems like fire or power, hit optimize, and compress weeks of manual floor-plan work into a single sitting. The founding team pairs Niklas Lindgren and Anton Juric—childhood best friends who previously sold a company in an adjacent space and grew up around MEP consultants—with David Rydberg and Gustav Hammarlund from Goldman’s low-latency trading desk in Stockholm. Investors describe the bet as AI fundamentally rewriting how engineering organizations operate [^1][^2][^1].

- **Sekai — $26M for consumer AI creation.** The round was led by Keith Rabois at Khosla Ventures and Nik Quinn at Connect Ventures, with participation from Mayfield, a16z speedrun, and A*. Founder lucky_z2 cites prior companies acquired by Apple and TikTok, and says Sekai’s no-code platform has already enabled 15M creations from a phone. Rabois called it the highest-potential consumer AI application since ChatGPT [^3][^4].

- **Gigascale Capital — $250M first institutional fund.** The new vehicle is aimed at early-stage founders rebuilding the physical economy. Sarah Guo publicly backed the firm’s physical-economy thesis and endorsed Schrep as a trusted technologist for early cap tables [^5][^6].

## Emerging Teams

- **Plena is the clearest traction signal among new launches.** The company positions itself as an AI OS for specialty medical practices, automating referrals, fax, scheduling, and collections end-to-end so doctors can focus on medicine. It says it grew 17x in eight months and crossed seven figures in contracted ARR. Founders are @eebadaeebada and Ahmed [^7].

- **Intelligence Factory is a robotics team to watch.** YC says it is building human intelligence for robots by training general-purpose manipulation models on human demonstration data across vision, action, and touch, then deploying them in warehouses, grocery stores, and data centers [^8].

- **Vertical AI operating systems are spreading into messy workflows.** Parrot is building an AI-native OS for auto repair shops whose agents can call real people using context across estimates, parts, customers, insurers, suppliers, and payments. Gravy connects to banks, investments, and email to explain money and automate financial tasks. Memoir turns code into demo videos and founder-voice social posts, while Bloom turns brand systems into infrastructure that agents can call [^9][^10][^11][^12].

- **Developer tooling is moving from copilots toward autonomous loops.** Ara describes itself as a self-driving IDE that ships features instead of waiting for prompts, using self-improving memory across the app, Claude, and Codex. BentoLabsAI is building a monitoring and learning layer for long-running agents and reports Sonnet 4.5 improving from 42.2% to 52.4% on its internal TB2 benchmark [^13][^14].

## AI & Tech Breakthroughs

- **Biohub released a major protein-model stack.** Biohub, founded by Priscilla Chan and Mark Zuckerberg, introduced ESMC, trained on about 2.8B protein sequences, ESMFold2, which it says outperforms AlphaFold 3 on some benchmarks, and ESM Atlas, covering 6.8B sequences and 1.1B predicted structures. In cancer and immunology binder-design experiments, the tools achieved 36–88% hit rates for compact minibinders and 15–29% for antibody-derived formats, with confirmed lab binding. The release also reports scaling-law behavior across model generations [^15].

- **MiniMax M3 is a notable new open-weight model.** It combines 59.0% on SWE-Bench Pro, 66.0% on Terminal Bench 2.1, 1M context through MiniMax Sparse Attention, and native multimodality from step zero. Weights and a tech report are expected in about 10 days [^16].

- **GPIC is a notable new permissive dataset for image-model builders.** The Stanford-led Giant Permissive Image Corpus offers 100M safety-filtered, deduplicated images with captions, restricted to permissively licensed sources such as CC BY and CC0, and is hosted on Hugging Face for research and commercial use [^15].

- **Gladia’s multilingual ASR router is a practical architecture worth tracking.** Instead of one large multilingual model, it routes audio between smaller monolingual models using Zipformer for streaming transcription, Silero VAD for speech boundaries, and SpeechBrain for language identification. The system rolls back to the last speech boundary when it detects a language switch, and reports about 13% WER on inter-utterance code-switching benchmarks at smaller size than tested alternatives [^17].

- **LangSmith Sandboxes signal a maturing stack for agent execution.** The product is now GA for safely running agent-written code in isolated runtimes with network controls, persistent state, and snapshot/restore. Harrison Chase’s view is that future agents will need to write and execute code [^18][^19][^18].

## Market Signals

- **The AI economy is scaling faster than conventional statistics make visible.** Import AI estimates nominal US AI GDP at about $250B in 2025, growing roughly 2,600% annually in quality-adjusted real terms, with compute spending rising from $37B in 2023 to $219B in 2025 and quality-adjusted AI output growing above 2,200%. The same writeup argues standard GDP misses much of this because prices are falling quickly and much of the impact sits in inference [^15].

- **Usage, model output, and revenue are still accelerating.** Exponential View notes 170 AI models released since September 2025, top models handling tasks four times longer than last year’s best, and quarterly token consumption tripling. It estimates sector revenue at $25B per quarter, with OpenAI rising from $1.7B to $6B and Anthropic from $400M to $4.8B, while quarterly capex commitments climbed 43% to about $158B and revenue doubling time improved to 0.73 years [^20].

- **The main caution flag is capex strain, not broad revenue deterioration.** Exponential View says only one of its five bubble indicators is red, but capex has already pushed economic strain above 1% of US GDP into the amber zone [^20].

- **Two investment themes recur across the startup flow: physical-economy AI and agent control layers.** Gigascale’s new fund explicitly targets founders rebuilding the physical economy, and Endra applies AI to MEP engineering for buildings and data centers. Separately, LangSmith Sandboxes, Orka, and PiQ all point to a new control stack around safe execution, approval gates, immutable logging, and signed audit trails for autonomous agents [^5][^6][^21][^2][^18][^19][^22][^23][^24][^25].

## Worth Your Time

- **[Endra founder thread](https://x.com/niklaslindgrenn/status/2061464492542750976)** — a good primary source on the financing, team formation, and the thesis that AI will rewrite engineering operations [^1].

- **[Sekai founder thread](https://x.com/lucky_z2/status/2061538655521706397)** — concise on founder pedigree and the 15M-creation consumer AI signal [^3].

- **[Mukil Loganathan’s LangSmith Sandboxes keynote](https://youtu.be/IIchUA5T3gs)** — a 20-minute walkthrough of how to run agent code safely [^19].

- **[Exponential View: Still no bubble](https://www.exponentialview.co/p/still-no-bubble)** — useful for separating real AI revenue growth from capex excess [^20].

- **[Import AI 459](https://importai.substack.com/p/import-ai-459-ai-oversight-is-difficult)** — strong synthesis on AI GDP measurement, Biohub’s protein models, and the GPIC dataset [^15].

---

### Sources

[^1]: [𝕏 post by @niklaslindgrenn](https://x.com/niklaslindgrenn/status/2061464492542750976)
[^2]: [𝕏 post by @a16z](https://x.com/a16z/status/2061468521935352238)
[^3]: [𝕏 post by @lucky_z2](https://x.com/lucky_z2/status/2061538655521706397)
[^4]: [𝕏 post by @rabois](https://x.com/rabois/status/2061554163352252697)
[^5]: [𝕏 post by @schrep](https://x.com/schrep/status/2061474431118229932)
[^6]: [𝕏 post by @saranormous](https://x.com/saranormous/status/2061528181488910521)
[^7]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061538273382846590)
[^8]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061508076235034757)
[^9]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061568471515701704)
[^10]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061553374676631666)
[^11]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061526376763777441)
[^12]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061462786274721890)
[^13]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061447675166240982)
[^14]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2061417480573141003)
[^15]: [Import AI 459: AI oversight is difficult; scaling laws for protein folding models; and pricing the extinction risk of AI systems](https://importai.substack.com/p/import-ai-459-ai-oversight-is-difficult)
[^16]: [𝕏 post by @MiniMax_AI](https://x.com/MiniMax_AI/status/2061266317815296322)
[^17]: [r/MachineLearning post by u/JeanMichelRanu](https://www.reddit.com/r/MachineLearning/comments/1ttwfuy/)
[^18]: [𝕏 post by @hwchase17](https://x.com/hwchase17/status/2061496556608504043)
[^19]: [𝕏 post by @LangChain](https://x.com/LangChain/status/2061448130806116827)
[^20]: [🔥 We checked. Again. Still no bubble.](https://www.exponentialview.co/p/still-no-bubble)
[^21]: [𝕏 post by @dhaber](https://x.com/dhaber/status/2061467679051940342)
[^22]: [r/SideProject post by u/MarzipanKlutzy9909](https://www.reddit.com/r/SideProject/comments/1tu65kt/)
[^23]: [r/SideProject comment by u/Mysterious_Anxiety86](https://www.reddit.com/r/SideProject/comments/1tu65kt/comment/op7ft71/)
[^24]: [r/SideProject comment by u/MarzipanKlutzy9909](https://www.reddit.com/r/SideProject/comments/1tu65kt/comment/op7biof/)
[^25]: [r/SideProject post by u/fred_pcp](https://www.reddit.com/r/SideProject/comments/1ttkxsy/)