Explore 3067+ AI Developers (page 84)
obeli-sk
To provide a fast, open-source, durable, and deterministic workflow engine that simplifies distributed systems and AI agent orchestration.
jammievae
To build a production-grade, multi-language AI agent platform with advanced reasoning, memory, and self-improvement capabilities.
Builder Methods
Training, tools, and community for business owners and operators building real apps, agents, and systems with AI without coding experience.
Stora
Stora automates mobile app store presence and releases using AI agents to generate screenshots, ASO metadata, and compliance reports while handling submissions to the App Store and Google Play.
hieunc229
hieunc229 is an independent developer building open-source tools on GitHub. Mailflare is their self-hosted email client project built on Cloudflare Workers, combining custom domain email routing with a planned AI agent layer. The project is written in TypeScript and targets developers who want full control over their email infrastructure.
BenedictKing
To provide a unified, secure, and reliable proxy gateway for AI API access and protocol conversion.
Udit Akhouri
Building safe, reliable AI infrastructure for healthcare and developer tools, focusing on preventing premature convergence in agents and enabling clinical autonomy.
deeplethe
deeplethe builds forkd, an open-source microVM sandbox runtime for AI agent fan-out workloads. The project focuses on collapsing per-request VM startup costs using Firecracker and copy-on-write memory snapshots. Written primarily in Rust and licensed under Apache 2.0, forkd targets self-hosted deployments where KVM isolation and sub-100ms spawn times are required without vendor lock-in.
Cosmic Stack
Cosmic Stack is a research and product lab building the agents, infrastructure, and tools of the next decade, focusing on closing the gap between technical AI possibilities and shipped products.
LearningCircuit
LearningCircuit builds Local Deep Research, an open-source, privacy-first AI research assistant that runs entirely on local hardware. The project supports all major local and cloud LLMs, integrates 10+ academic and web search engines, and keeps all data encrypted on the user's machine. Development is community-driven, with contributions tracked on GitHub and benchmarks maintained on Hugging Face.