# Ami Labs, Agave, and Surtr Lead This Week's Early-Stage Signals *By VC Tech Radar • July 8, 2026* Fresh rounds in construction AI, counter-drone defense, and quantum are paired with a new world-model push from Ami Labs. The broader signals point to sovereign AI demand, configurable AI layers, and startups being built to manage AI's side effects. ## Funding & Deals - **Agave — $15M Series A.** Agave is bringing AI to construction's back office, automating invoice processing, job costing, and financial reconciliation across disconnected systems. The company says it has 500+ customers, nearly $100B of construction volume on platform, two years of profitability, and revenue that nearly tripled year over year. [^1] - **Surtr Defense — $4.8M seed.** Surtr combines sensors, radars, and effectors into one interface and can automatically cue a response to incoming threats. YC says the system was tested in Ukraine and detected and tracked FPV drones with under 100ms latency. [^2] - **Oratomic — Khosla's largest initial investment to date.** Vinod Khosla says Khosla Ventures made its largest initial investment yet into Oratomic after evaluating a dozen quantum startups over a decade. The target is a fault-tolerant quantum computer capable of solving Shor's algorithm and supporting useful applications. [^3] ## Emerging Teams - **Ami Labs.** LeCun described Ami Labs as a France-based global company centered on world models. The company draws on the FAIR Paris talent pipeline and a team already spread across Paris, New York, Montreal, and Singapore; it is hiring researchers and engineers and expects industrial collaborations around JEPA/world-model applications. Its investor base is roughly 40% European, 33% U.S. including Jeff Bezos and Greycroft, and 27% Asian. [^4] - **Perfectvector.** Two former image-model researchers with PhD/MS backgrounds say they have spent six months full-time building a model from scratch that turns PNG or JPG inputs into editable SVGs. They claim roughly 70% fewer nodes than standard tracers on their test set, and the product is free for now because GPU costs are high and the team wants feedback. [^5][^6][^5][^7] - **PromptShielder.** PromptShielder masks names, emails, salaries, and IDs in the browser before text is sent to ChatGPT or Claude, then restores the originals locally on the way back. The founder frames it as a response to enterprise leakage risk after seeing HR staff paste sensitive termination letters into ChatGPT; the tool has no backend, logs, or stored prompts. [^8] ## AI & Tech Breakthroughs - **World models are being positioned as a post-LLM frontier.** Ami Labs' approach is to learn predictive representations of the physical world via JEPA rather than reconstructing pixels or tokens. LeCun says the world-model stack uses SIGREG and pushes for statistical independence, not just decorrelation, inside joint-embedding methods. [^4] - **Model-based vectorization may beat tracer cleanup for AI imagery.** Perfectvector says classic tracers follow pixel boundaries, which makes anti-aliased AI renders hard to simplify cleanly, so the team stopped building on top of tracers and trained a model instead. The current target is illustrations, logos, stickers, and other flat-ish art rather than photos or painterly renders. [^5] - **Deterministic AI analytics is emerging as a design pattern.** One solo founder's analytics product lets users ask questions in plain English from a dashboard or through Claude/MCP, but the AI can only call the same deterministic reports the dashboard renders, and CI fails if the two ever diverge. The product is aimed at small SaaS teams that find Mixpanel or Amplitude expensive and want tighter data control. [^9] ## Market Signals - **Sovereign AI positioning is becoming a commercial wedge.** LeCun says industry and governments want a frontier AI supplier that is neither American nor Chinese, which is part of why Ami Labs is headquartered in France. [^4] - **This set again favors vertical AI with measurable workflow outcomes.** Agave's Series A is tied to construction accounting automation, and the company says it already has 500+ customers, nearly $100B of construction volume on platform, two years of profitability, and revenue that nearly tripled year over year. Elizabeth Yin also highlighted pre-seed investor Pat Matthews as focused on AI-native business software. [^1][^10] - **Configurable AI layers are showing stronger usage than fixed feature roadmaps in at least one enterprise case.** One startup says it stopped building standard enterprise features and instead let customer ops teams build their own tools inside the app with an LLM-based builder. It reports 90% activation on those custom tools with no training and 89% day-30 retention. [^11] - **New startups are targeting AI's side effects, not just model output.** Slopfix says clients arrive with 100k-line AI-generated codebases, so it commits to reduction targets and charges in proportion to code removed, while PromptShielder targets the opposite problem of employees sending sensitive documents to external LLMs despite company bans. [^12][^8] > We get paid to delete code. [^12] ## Worth Your Time - **[LeCun on post-LLM world models](https://www.youtube.com/watch?v=m7ywFu3Yqh8)** — Primary-source discussion of JEPA, SIGREG, and Ami Labs' geopolitical positioning. [^4] [![Les Worlds Models : l’IA post LLM, expliqué par Yann LeCun](https://img.youtube.com/vi/m7ywFu3Yqh8/hqdefault.jpg)](https://youtube.com/watch?v=m7ywFu3Yqh8&t=1396) *Les Worlds Models : l’IA post LLM, expliqué par Yann LeCun (23:16)* - **[Perfectvector founder post](https://www.reddit.com/r/SideProject/comments/1uqi6ay/)** — Technical explanation of why tracer-based cleanup failed and why the team trained a model instead. [^5] - **[Slopfix founder post](https://www.reddit.com/r/SaaS/comments/1uq8fr1/)** — Founder essay on pricing refactors against code deletion in AI-generated codebases. [^12] - **[Khosla on Oratomic](https://x.com/vkhosla/status/2074500781311680846)** — Short statement of why Khosla Ventures made its largest initial quantum investment after reviewing the category for a decade. [^3] --- ### Sources [^1]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2074512939193880789) [^2]: [𝕏 post by @ycombinator](https://x.com/ycombinator/status/2074635905567174974) [^3]: [𝕏 post by @vkhosla](https://x.com/vkhosla/status/2074500781311680846) [^4]: [Les Worlds Models : l’IA post LLM, expliqué par Yann LeCun](https://www.youtube.com/watch?v=m7ywFu3Yqh8) [^5]: [r/SideProject post by u/tamingunicorn](https://www.reddit.com/r/SideProject/comments/1uqi6ay/) [^6]: [r/SideProject comment by u/tamingunicorn](https://www.reddit.com/r/SideProject/comments/1uqi6ay/comment/ow8dydf/) [^7]: [r/SideProject comment by u/tamingunicorn](https://www.reddit.com/r/SideProject/comments/1uqi6ay/comment/ow8d5l5/) [^8]: [r/SideProject post by u/Horanyi](https://www.reddit.com/r/SideProject/comments/1uq99j0/) [^9]: [r/SaaS post by u/PotatoRamen72](https://www.reddit.com/r/SaaS/comments/1upxx76/) [^10]: [𝕏 post by @dunkhippo33](https://x.com/dunkhippo33/status/2074552030572462166) [^11]: [r/startups post by u/namanyayg](https://www.reddit.com/r/startups/comments/1uq335d/) [^12]: [r/SaaS post by u/zie1ony](https://www.reddit.com/r/SaaS/comments/1uq8fr1/)