Foxglove has launched “Data Search and Curation”, a new set of capabilities that helps robotics teams replace fragmented, manual data workflows with a unified platform to find and curate the mission-critical events, anomalies, and system behavior that matter most across growing volumes of operational data.
The company also expanded the Foxglove Data Platform with Bring Your Own Storage (BYOS), a new self-hosted data lake deployment model allowing customers to maintain full control over data at rest while still providing the benefits of a fully managed database, and a new free Basic Seat tier to expand access to visualization across teams.
As robotics companies scale from prototype to production, the critical path is shifting from generating more data to finding the most essential data quickly enough to debug issues, investigate failures, review safety-critical events, and improve system performance.
Foxglove’s latest product updates are designed to address that shift by enabling teams to inspect more data faster, bring more people into key workflows, and support more flexible operations across complex deployments.
Adrian Macneil, co-founder and CEO, Foxglove, says: “Robotics teams are generating more data than ever, but the real challenge is finding the critical 1 percent that drives improvement in the real world.
“Companies that win in physical AI are the ones with the strongest data flywheel, turning production robot data into better decisions, faster model improvements, and new robot capabilities.
“Data Search and Curation helps teams uncover that high-value 1% faster so they can learn faster and improve robot performance in the real world.”
Find the data that matters faster
Foxglove is launching Data Search and Curation to help robotics teams find, organize, and operationalize data more effectively.
With Data Search, users can directly query multimodal robotics data, making it faster to identify events of interest without needing to preprocess or ingest data into a separate data warehouse.
New data curation capabilities help teams tag, annotate, and enrich events, making it easier to preserve key findings, build training and validation datasets, and support repeatable analysis across programs.
Together, these capabilities help robotics developers improve iteration speed, streamline collaboration, and turn growing volumes of robotics data into actionable insights.
For teams operating in complex or safety-critical environments, faster access to relevant data can accelerate debugging, model training, validation, and overall system improvement, strengthening the data flywheel that helps teams learn faster and improve systems over time.
Shared visibility across teams
Foxglove is introducing a new free Basic Seat tier to make it easier for robotics organizations to extend access beyond engineering to teams involved in QA, triage, safety review, and management. Basic Seats give more stakeholders direct visibility into robot behavior, system performance, and operational events.
By giving more teams access to the same data and workflows engineering relies on, Basic Seats help organizations reduce handoff friction, accelerate issue investigation, and improve alignment across development and operations.
The result is a more scalable way to support collaboration, speed decision-making, and bring the right people into critical workflows as robotics programs grow.
Enterprise-grade data control, without the complexity
Foxglove is introducing BYOS, a bring your own storage deployment model that gives enterprise robotics companies more control over how their data is stored and managed without needing to manually provision cloud infrastructure.
With BYOS, customers host all multimodal log data in their own cloud object storage, while Foxglove provides the managed compute and services to make that data usable, including indexing, query, search, evaluation, and metadata workflows.
For enterprise teams, BYOS offers the ability to scale Foxglove in environments with stricter data, infrastructure, or residency requirements.
It gives customers tight control over their data while reducing the operational burden that comes with running a self-hosted Kubernetes deployment.
The result is a more flexible deployment model that helps organizations move faster without compromising on enterprise requirements.
One platform to manage the physical AI data lifecycle
Together, these product updates reflect Foxglove’s evolution from observability into a comprehensive physical AI data platform to capture and learn from all types of multimodal data.
As the industry scales, Foxglove will continue to expand the platform to help customers turn growing volumes of robotics data and deployment complexity into faster decisions, better performance, and a stronger path to production.
