Viam is built for software engineers building for the physical world. Write in languages you know. Connect any hardware. Prototype fast. Scale without a rewrite.
$10,000 in platform credits
2 hours/month engineering office hours
Direct line for support
Ship your prototype in days, not months.
Build and debug from anywhere. Write in Python, Go, TypeScript, or Flutter. Connect to your robot over the network, stream logs, view sensor data, and teleoperate from the browser, no VPN or SSH.
Hardware is complex. Your code shouldn’t be.
Declare hardware in JSON. Viam handles drivers, initialization, and a consistent API. Same interface for every device. Swap hardware without rewriting code. Your logic runs locally, so it works even offline.
Data is your moat. Build it from day one.
Automatically capture, sync, and label sensor data from your fleet. No custom ingestion scripts. Turn every robot into a closed-loop learning system that continuously improves your models.
Code that scales with you.
Prototype code runs your fleet. Push updates instantly, roll back easily. Every machine feeds your models, so your fleet gets smarter as it grows. No rewrites, no migrations, no rebuilding at scale.
Don't burn your seed round on infrastructure. Credits cover your first machines, data sync, and fleet management — meaningful runway from day one. Credits must be used within one year of starting.
2 hours/month engineering office hours
Scheduled time with the engineers who built the platform. Bring your architecture questions, your roadmap, your hardest technical decisions. Proactive help, not reactive support.
Direct line for support
Not a ticket queue. Not a chatbot. We set up a shared Slack channel so you're always one message away from someone who can actually help.
* Available for qualifying pre-seed to Series A startups building hardware products.
Most stacks break between 1 and 10 machines. Viam doesn't.
Your prototype code runs your fleet. No rewrites, no migrations, no rebuilding at scale.
Prototype: Idea → demo in days. No custom infrastructure.
Pilot: 1 → 50 machines. Same config, no rewrite.
Fleet: 50+ machines. OTA updates, monitoring, and rollbacks built in.
Cut time-to-market by 50%. Deploy software updates 90% faster. Scaled from prototypes to thousands of robots, without rebuilding the stack.
Built a multimodal AI cooking assistant from scratch — and shipped it — without a traditional robotics engineer on the founding team.
Shipped an AI-powered grill in under a year while the Viam platform handled authentication, OTA updates, model deployment, and data pipelines.
UBS Arena built an AI-powered fan experience feature in 10 days using existing cameras and no new hardware.
Open source. No black boxes.
The core RDK is open source on GitHub. No black boxes, no vendor lock-in. Use the Viam Registry for instant access to drivers and ML models, and keep your proprietary logic private.
The Startup Stack: Custom vs. Viam
Feature
The Custom Headache
Viam
Hardware Integration
Hunting for 5-year-old GitHub repos and debugging C++ build errors for every sensor.
JSON config. Declare your hardware, pull the driver from the Registry, and start coding.
AI/ML Deployment
Fighting CUDA drivers and "library hell" on the edge just to get a model to run.
Deploy PyTorch/TF models with a toggle. Call inference via a clean API.
OTA Updates
"The Golden SD Card" or brittle Ansible scripts. Praying the update doesn't brick the unit.
Push updates to one robot or the whole fleet. One-click rollbacks if things go sideways.
