VIAM

Unlocking data & AI in the physical world

Viam is the easiest way to bring data, AI, and automation into your business. Add cutting-edge capabilities to existing systems, and build new ones fast.

Final Outcomes

Outcomes:

• $30 million series C with $117 million raised to date.

• 40+ B2B partnerships.

• $16 million in projected revenue for 2025.

• Active community of over 2,750 smart machine developers.

• Over 23k machines created

• Reduced configuration time by 65%, based on average rover setup times.

Trusted by

Company Overview

Viam has been working since 2019 to create a new standard for hobbyist developers developers to Fortune 500 businesses to configure, launch, control, and monitor their fleets of IoT and robotic devices.

To leverage the full power of Viam’s ecosystem of products, from data aggregation, machine learning models, and a registry of compliant components, users need a way to efficiently configure and test their new smart machines. Machine configuration acts as the core of the VIAM platform which other product services such as Fleet Management, Data, Machine Learning, & Registry derive their ecosystem level value from.

ⓧ Design/technical debt
Two years of features and development needed to be evaluated as a whole.

ⓧ Leverage industry best practices
Users prefer websites or applications to function in the same way as other sites they are familiar with.

ⓧ Streamlined user flows
Combine several complicated and separated user flows into a more cohesive experience.

Success Metrics

Before starting the design process I aligned with senior leadership on metrics to define the future success of the project:

1. It increases product adoption by enterprise customers.

2. It reduces configuration time for solutions engineers.

3. It integrates UI patterns common in developer platforms.

Research & Discovery

Competitive Analysis ROS

We looked into several leading competitors in the robotics and IoT spaces to align on feature parity and industry best practices.

Competitive Analysis IDEs

Key Insights

1. File-tree navigation is essential: Developers expect to see a structured, nested view of machine components, similar to IDEs or JSON structures they're familiar with.

2. Configuration needs to be readable and editable: Users wanted clear machine definitions they could read at a glance — and the flexibility to edit settings inline or via raw JSON when needed.

3. Separation of setup and operation is critical: Many platforms confuse configuration with live control. Users wanted to configure safely before deployment — not while the robot is running.

4. Familiar UI patterns reduce ramp-up time: Competitor tools like ROS and Intrinsic often rely on complex CLI tools or XML files. Viam’s web-based UI had an opportunity to stand out with familiar UI/UX conventions.

5. Debugging needs to be integrated: Users expected to see real-time logs, validation warnings, and machine state summaries during configuration to reduce guesswork and deployment errors.

Ideation & Conceptualization

Flow mapping

Wireframing

The design needed to allow users to scale the configuration to as many or few parts and resources as they need.

I put together low-fidelity wireframes to visualize the flows, layout and structure allowing us to test the simplicity and experience of the product to gain early feedback and make improvements before moving to detailed designs. This highlighted a need for users to be able edit choices once results were generated to refine the outputs.

PRIME Design System

As part of a larger effort to align engineering teams with design the PRIME library was migrated to a more robust platform to support additional documentation. Pattern examples and best practices were added, along with pages the new components which were built for the redesign.

Key Final Screens & Features

Null State

Adding Resources

Fully Configured Machine

JSON Configuration

Frame Configuration

Logs

Connect

Reflections & Learnings

What Went Well

📈 Higher engagement with both business and consumer customers

💡 Reduced effort for our solutions engineering team members

⏱️ Reduced times for task completion

🧩 Integration of long-standing and blocked backlog items

Conclusion

Based on the initially defined success metrics, the configuration redesign was able to:

1. Increased product adoption.

   • Improved configuration was directly cited for closing 2 clients (Tennibot & Billion Oyster Project) which had been indecisive about using Viam before the redesign.

2. Reduced configuration time.

   • After testing, we found an average 42% configuration time reduction using Viam rovers

3. Integration of common developer UI patterns

   • By introducing a component tree, version history, & a JSON view we collected qualitative feedback from users that the app more closely matched their expectation for developer tooling.