Ship reliable robots, at any scale.

Roboto analyzes your robotics data, so you know how your robots behave, why they fail, and what to improve.

Teams building robots from prototype to production trust Roboto.

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"We can preemptively find complex hardware and software issues across our fleet before they become a problem for our customers."

Walker Robb, VP Eng · BRINC

"Roboto is the first place we go when one of our robots has an issue. It has significantly reduced the time and cost required for our team to investigate failures and identify root causes."

Aaron Roller, Head of Software Infrastructure & Reliability · ANYbotics

"Roboto makes it easy to diagnose issues on a single dataset or zoom out to aggregated metrics."

Konrad Leibrandt, Dir. Algorithms · Telos Health

"Reviewing procedure runs manually was never going to scale. Now we describe the moments we care about, and Roboto curates them into Collections we can evaluate and train on, accelerating how we develop and validate new Physical AI capabilities…"

Ritwik Ummalaneni, Head of Data Intelligence · Moon Surgical

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Overview

Robotics teams are drowning in data. Roboto surfaces what matters, automatically.

Automate your analysis

Manual replay tools don't scale as data grows. Create workflows to analyze logs automatically.

Search for patterns

Find critical events, anomalies and edge cases hiding in your robotics data.

Curate new datasets

Turn multimodal robotics logs into structured datasets for training and evaluation.

Track your reliability

Create custom metrics to track performance across your fleet as you scale.

Go from raw logs to root cause.

Roboto finds problems before your customers do.

Read every robotics format. Ingest your logs and get back indexed datasets ready for querying, all through a single Python SDK.

Analyze

Process your raw data into metrics. Use Actions and Triggers to automate your workflows and aggregate fleet-level KPIs.

AI Summary

A PX4-based drone operated in Lingfield, England, starting at 2025-08-21T10:35:48Z. The flight lasted approximately 132 seconds, with the vehicle experiencing significant sensor and estimation challenges. The drone was equipped with a CubePilot CubeOrange flight controller running PX4 firmware.

Key Events

• High Vibration Levels : Mean vibration of 16.58 m/s², max of 40.42 m/s², indicating potential stability and sensor accuracy issues.
• GPS Jamming : GPS jamming indicator elevated, with mean of 52.19 (threshold is 40), suggesting potential signal interference.
• GPS Position Accuracy Issues : Horizontal position accuracy exceeded recommended threshold, with a mean of 3.46 meters.
• Estimator Faults : Bad vertical accelerometer data detected across multiple estimator instances, potentially affecting estimation accuracy.

Critical Issues

Estimator Filter Fault(@ ~2024-12-23 17:31:43 UTC)

• The primary EKF changed due to filter fault - this is a serious navigation issue
• Bad vertical accelerometer data detected for ~65 seconds across all three estimator instances
• This compromised the drone's ability to accurately determine its position and attitude

Blind Land Failsafe Triggered(@ ~2024-12-23 17:32:44 UTC)

• Failsafe activated: blind land mode
• The system detected invalid setpoints and had to switch to emergency landing
• The drone likely stopped working at this time (2024-12-23 17:32:44 UTC) due to this failsafe activation

Critically High Vibration Levels

• Mean vibration: 29.15 m/s², max: 79.08 m/s² (critically high above 9.81 m/s²)
• Extensive sensor clipping on all axes (accelerometers and gyroscopes)
• This severe vibration likely contributed to the estimator faults

GPS Issues

• Elevated GPS jamming (mean: 52, max: 60 - should be below 40)
• Poor horizontal accuracy (should be <1m)
• GPS reboot due to undervoltage detected

Agents analyze data for you. Automate triage, root cause analysis and event detection. Review insights not raw logs.

Find the signals in the noise. Search metadata, tags, topics and events. Match patterns in signals across petabytes of data.

Turn raw recordings into curated datasets. Extract the slices of data worth training on. Organize them into Collections and export to any pipeline.

Industries

Built for industries where uptime and reliability matter.

A single failure can ground a fleet.

Roboto analyzes every flight so your team catches issues before customers do, and builds the FAA Part 108 audit trail. Whether you fly for public safety, delivery, or defense.

• Ingest every drone format

Support for PX4, ArduPilot, ROS, CSV, JSON, Parquet, system logs and your team's custom formats.

• Search your entire flight archive

Slice through thousands of flights by hardware configuration, software version, or mission events. Zero downloads required.

• Catch the issues you don't want to miss

Surface issues and anomalies like vibration spikes, GPS jamming, magnetometer drift, sensor clipping, and failsafe activation.

• Automated QA on every unit

Battery health, sensor fusion, GPS, motor performance. Catch issues at the factory, not in the field.

Medical devices & surgical robots

One failure is too many.

Roboto analyzes every procedure so your team catches anomalies before surgeons do. Whether you are validating in R&D cadaver labs or deploying in operating theaters.

• Multimodal playback, time-synced.

Synchronize video, robot telemetry and system logs into one unified view with key events highlighted.

• Dive deep or zoom out.

Investigate one procedure in detail, or aggregate metrics and faults across all devices and releases.

• Every procedure becomes training data.

Slice long recordings into episodes, group them into Collections, and export to training formats.

• Audit trail for regulators.

Every analysis runs through repeatable, version-controlled pipelines. Prepare evidence for FDA review and 510(k) submissions.

Autonomous vehicles

Your fleet drives more miles than your team can ever review.

Every disengagement is an investigation that needs to be triaged. Find the anomalies before they become fleet-wide issues.

• Multimodal at scale.

Ingest data from LiDAR, camera, radar, and other sensors. Trace issues across subsystems.

• Pattern search across every drive.

Flag important moments and find other similar occurrences across millions of miles.

• Fuel your training flywheel.

Mark events on drives, group them into Collections, and export to training formats.

• Disengagement triage, on autopilot.

Roboto's agents determine the failure mode and potential root cause for every disengagement, and tag them in your issue tracker.

One SDK. Every log format.

Use the Roboto SDK to start reading ROS, PX4, MCAP, and Parquet files through one Python API. Use it in your notebook, in CI, or on every new upload.

from roboto import Dataset

ds = Dataset.from_id("ds_9ggdi910gntp")
bag = ds.get_file_by_path("scene57.bag")
steering = bag.get_topic("/vehicle_monitor/steering")

# Same call works for ROS bags, ULogs, MCAP, and Parquet
data = steering.get_data(
    start_time="1714513576",
    end_time="1714513590",
)

from roboto import RobotoSearch

search = RobotoSearch()

# Find drives in Boston where vehicle_speed exceeded 20mph
query = """
dataset.tags CONTAINS 'boston' AND
topics[0].msgpaths[/vehicle_monitor/vehicle_speed.data]
    .max > 20
"""

results = search.find_files(query)
for f in results:
    print(f.file_id, f.relative_path)

from roboto import query, RobotoSearch, Event
from roboto.analytics import find_similar_signals

search = RobotoSearch()

# Reference signal from an existing Event
event = Event.from_id("ev_6funfjngoznn17x3")
query_signal = event.get_data_as_df(
    message_paths_include=["linear_acceleration"],
)

# Find every other log that exhibits the same pattern
topics = search.find_topics("topic.name = '/snappy_imu'")
matches = find_similar_signals(
    query_signal,
    topics,
    max_matches_per_topic=1,
    normalize=True,
)

from roboto.domain.actions import (
    Trigger,
    TriggerForEachPrimitive,
)

# Run analyze_grasp_performance automatically on every new .bag
trigger = Trigger.create(
    name="auto_process_grasp_bags",
    action_name="analyze_grasp_performance",
    required_inputs=["**/*.bag"],
    for_each=TriggerForEachPrimitive.Dataset,
)

• Any robotics format.

ROS, PX4, MCAP, Parquet, JSON, CSV, Journal and custom formats.

• Query the entire fleet.

Filter by metadata, topic statistics, and signal patterns.

• Every log is training data.

Slice episodes, curate Events, export to formats like LeRobot.

• From notebook to production.

Same Python runs as an Action on every new upload.

How teams ship reliability with Roboto.

Case studies, engineering write-ups, and field notes from robotics teams in production.

Stop reacting to failures. Start preventing them.

Analyze every log. Surface failures. Start with your next upload.

Common questions about Roboto.

What is Roboto?

Roboto is the analytics engine for Physical AI. We ingest every robotics log format and automate robotics data analysis so you can understand robot behavior, diagnose failures, and improve system performance.

How is Roboto different from a log visualizer?

Visualizers show you one log at a time. Roboto analyzes every log, flags the issues that matter, and lets you query patterns across your entire fleet. You start with the answer, not a timeline.

How does Roboto work?

Roboto reads your logs from your bucket or upload, indexes every topic and event, runs configurable agents and deterministic health checks against each one, and surfaces results. The same Python SDK powers ad-hoc analysis and production Actions.

What file formats does Roboto support?

Roboto supports multimodal data stored in ROS bags, PX4 (ULog), ArduPilot (bin, log, tlog), MCAP, Parquet, CSV, JSON, Journal, video (MP4, MKV, AVI), and custom binary formats. Add a new format in a few lines of Python and the rest of the platform inherits it.

Where is my data stored?

You choose. Connect an AWS S3 bucket and Roboto indexes and reads from it directly. For teams that prefer it, we also offer fully-managed storage in our cloud or your VPC.

How does Roboto handle enterprise security and deployment?

Roboto connects to your existing SSO over SAML or OIDC, with role-based controls that scope access by user, team, and dataset. Run Roboto in our cloud or self-hosted inside your own AWS environment. Every action is logged with retention windows you control, so the security and compliance posture your team already runs continues to apply.