In a world where AI feels like it lives somewhere “out there” in the cloud, one startup is flipping the script. RunAnywhere, a YC-backed venture founded by Sanchit Monga and Shubham Malhotra, is redefining how artificial intelligence interacts with everyday devices by making on-device AI not just possible, but practical. The founders believe the future of AI isn’t confined to distant servers or massive data centers, it belongs in our pockets, laptops, and embedded hardware, running instantly, privately, and reliably.
The On-Device AI Moment Is Here
The surge in AI adoption has highlighted a critical gap: cloud-first models deliver impressive demos but often struggle in real-world environments. High latency, privacy concerns, unreliable connectivity, and mounting cloud costs are pushing AI closer to the user—literally onto their devices.
According to the founders of RunAnywhere, this shift marks a fundamental change in how AI-powered products will be built. From smartphones to edge hardware, they envision a future where on-device AI becomes the default for interactive experiences, especially voice-driven applications.
“Latency is a feature. Privacy is a feature. Reliability is a feature,” the founders explain. “On-device AI is how you deliver all three at once.”
By bringing AI directly to the device, RunAnywhere aims to enable applications that feel faster, safer, and more dependable without constant reliance on cloud infrastructure.
Solving the Hardest Part of Edge AI
RunAnywhere isn’t just tackling inference; it’s tackling distribution, updates, and fleet management, the real bottlenecks for edge AI. Shipping models to millions of devices isn’t as simple as embedding a model file; it involves memory constraints, hardware diversity, runtime compatibility, and OTA updates. Sanchit’s experience as a mobile developer at Intuit gave him firsthand insight into these challenges. “The reality is that ‘it works on my machine’ doesn’t matter if it can’t ship smoothly to millions of devices,” he notes.
One SDK, Infinite Inference
At the core of RunAnywhere’s platform is a unified SDK that allows developers to integrate once and deploy models across iOS, Android, and edge devices. Through the control plane, teams can manage model versions, rollout policies, and observability across thousands of devices. This approach transforms AI deployment into a developer-friendly experience akin to calling a cloud API but with the speed and privacy of local compute.
Voice AI: The Killer App for Edge
RunAnywhere’s infrastructure shines in on-device voice experiences. Always-on wake word detection, low-latency speech-to-text, and offline or hybrid LLM execution are no longer just aspirational, they’re shipping. Shubham explains, “Voice is unforgiving; users notice latency immediately. Our focus on optimization, routing, and practical engineering makes AI feel instant and private.”
Building for the Real World
The startup’s journey has been about translating conviction into production-ready infrastructure. Sanchit and co-founder Shubham iterated through developer pain points: packaging, updates, fallback logic, and analytics. Getting into Y Combinator validated the urgency of their mission. Today, RunAnywhere pilots with consumer hardware and enterprise partners, proving that on-device AI isn’t just theoretically possible, it’s scalable.
A Vision for the Future
RunAnywhere envisions a world where AI is always available, locally executing most tasks while leveraging the cloud selectively. Shubham sees a future where voice is the most natural interface, working offline when necessary, never compromising privacy. “The future default is not cloud AI or device AI. It is on-device-first with the cloud as a fallback,” he asserts.
Inspiration for Builders
For the founders, the biggest takeaway is the value of solving unglamorous infrastructure problems. “Constraints are design inputs,” he explains. “When AI becomes dependable on-device, entire product categories unlock.” By focusing on reliability, privacy, and latency, RunAnywhere is shaping the next wave of edge AI, proving that infrastructure-first thinking can change how people interact with technology.
