Talo Request a pilot

Robot training data, recorded in the real world and labelled to your rules.

Checked recording by recording, delivered ready to train on. Use collection, annotation or both.

Request a pilot See collection
action: pour

Partners

TanahLabs VR Oxygen
Records
1.5M+
Hours recorded
11,900+
Total size
76 TB+
Partners
4

Problem

Robotics researchers are data constrained.

Labelling 10 hours of video takes millions of boxes. Talo gets you training-ready data quickly.

One frame: two robot hands beside a toaster, with boxes around both hands and the toaster.
  1. 10 hoursof video
  2. 1,080,000 frames30 a second
  3. 3,240,000 boxes3 a frame

What we do

Two products, used alone or together.

  1. Source
  2. Check
  3. Label
  4. Deliver
CollectionWe find it, then label it
You send footage
AnnotationWe label it

Collection

The best data set for your task.

  • Egocentric
  • Multi-view
  • Third person
  • Phone POV
  • Fixed camera
  • Four partners
See collection
Head-camera frame of a robot hand holding a can over a blue bin, with labelled boxes around the hand, can and bin. action: place

Annotation

Your recordings, labelled in your schema.

  • Boxes
  • Tracks
  • Action segments
  • Task descriptions
See annotation

Partner marketplace

Find the best robotics data sets through one request.

Tell us the task. Talo routes it to the partner with the best data for it.

Before

You chase every vendor

  • Egocentric
  • Multi-view
  • Third person
  • Phone POV
  • Fixed camera

After

Talo finds the best data set

  • Egocentric
  • Multi-view
  • Third person
  • Phone POV
  • Fixed camera
See collection

How it works

You check the data fits before anyone records at volume.

Write the task list

One short script per task. Already have footage? Skip to step 4.

task:     pour water
start:    bottle upright on the table
end:      bottle back on the table
may vary: cup position, fill level, room

Test a pilot week

Load a small batch into your training code before any larger order.

scope:    a few tasks, a few locations
time:     one week
your job: load it, train on it, decide

Partners record

In places matched to your list.

capture:  head camera | phone | fixed camera
sites:    matched to your task list
consent:  on record for every contributor

Check and label

From our public sample clip.

tracks:   right hand, bottle, cup
segments: grasp, tilt, pour, return
check:    28 frames, 9 corrections logged

Receive weekly batches

In your format, with the rules and a check log.

format:   your schema; Parquet and MP4 by default
rules:    included with each batch
check:    log included with each batch
access:   private, access-logged repository

Quality

Every batch shows how it was made.

Check a labelled sample
What ships with each batch
  • recordings/Passed the intake check
  • labelsIn your schema
  • rulesAction names, start and end of each segment
  • check logFrames checked, corrections made
  • consentOn record, for collected data

Case studies

How a research lab and a startup got months of data work done in weeks.

Case study · Collection3 min A robotics startup gets household demonstrations from 30 homes it could not reach. 6,200 episodes · 30 homes · 8 weeks Case study · Annotation3 min A university research lab clears a 3,400-episode backlog and moves its old labels to a new 14-action list. 3,400 episodes · 5 weeks · 2.1% rework

Tell us what you're training and what data you have.

Start with a pilot before any larger order.

Request a pilot Browse partners