S1MS deploys and coordinates agentic LLM workloads across phones, SBCs (Pi/Jetson class), and IoT gateways. A lightweight Raft control plane manages updates, policy, and secure messaging while agents run locally on CPU/TPU/NPU.
Live, accessible SVG • Animated data flow
Edge privacy, latency, and cost beat cloud for many LLM tasks. Agents must work on commodity hardware.
Raft control plane + tiny agent runtime (WASM/ONNX). OTA updates, policy, and secure messaging.
Retail, field ops, industrial IoT, healthcare, and privacy‑sensitive apps.
Register an agent, deploy to a device profile, stream tokens back over MQTT/WebRTC, and collect traces.
POST /v1/agents
{
"name": "summarizer",
"model": "s1ms/qwen2-1.5b-gguf-q4",
"tools": ["web", "kv"],
"profile": "edge-1gb",
"transport": "mqtt"
}
POST /v1/deployments
{
"agent": "summarizer",
"target": {"group": "store-floor"}
}POST /v1/agents/summarizer/invoke?stream=true
{
"input": "Summarize: ...",
"context": {"customer_id": "123"}
}
# <= chunks over SSE/MQTT/WebRTCWe're building the future of edge AI — where intelligent agents run locally on everyday devices, ensuring privacy, reducing latency, and cutting costs while maintaining the power of modern LLMs.
To democratize AI by making powerful LLM agents accessible on resource-constrained edge devices. We believe the future of AI is distributed, private, and runs where the data lives — not in distant clouds.
A world where every smartphone, IoT gateway, and edge device can run sophisticated AI agents locally, creating a resilient, privacy-first AI ecosystem that works offline and scales globally.
Chief Executive Officer
Visionary leader with deep expertise in distributed systems and edge computing. Passionate about bringing enterprise-grade AI to resource-constrained environments. Previously scaled edge infrastructure solutions and has a proven track record in building developer-friendly platforms that solve real-world problems.
Chief Technology Officer
Technical architect specializing in distributed systems, ML optimization, and embedded computing. Expert in Raft consensus algorithms, quantized model deployment, and building resilient infrastructure that works in challenging network conditions. Drives the technical vision behind S1MS's innovative edge AI runtime.
Your data stays on your devices. No cloud dependencies, no data leaks, no compromises.
Clean APIs, comprehensive docs, and tools that just work. Built by developers, for developers.
Contributing to open standards, sharing knowledge, and building the future together.
We're always looking for talented engineers, researchers, and visionaries who share our passion for bringing AI to the edge. Interested in working with cutting-edge technology that will define the next generation of AI infrastructure?
Get early access, device benchmarks, and deployment playbooks for < 2GB RAM targets.
Start 3+ control nodes (Raft). Devices auto‑join via token and receive OTA agent bundles.
Linux SBCs, x86 mini PCs, Android, and any WASM/ONNX capable target. No GPU required.
Yes—agents execute locally; control plane tolerates partitions and syncs when links return.
mTLS between nodes, per‑device policies, signed artifacts, and optional TEEs.