A gloved hand seats a connector on a cable harness board. A blue glow marks the fingertip force.

FIG.01 Tactile data for robots

Robots learn by watching.
They master by feeling.

Taktil captures how skilled hands feel, move and see during real industrial work, and turns it into training data for robots.

  1. 01Skilled worker works
  2. 02Taktil captures
  3. 03Robot learns

Robot shown for illustration. Taktil does not build robots.

02 / Why touchFailure modes, observed

Video is not enough.

( 01 )

Cameras see motion, not force.

Seating a connector, routing a cable or clipping a harness depends on forces no camera records.

( 02 )

Staged tasks miss the real world.

Real production brings the variance, mistakes and recoveries robots meet on the line.

( 03 )

Provenance is now required.

Buyers need to know where data came from, who agreed to it, and how it was documented.

03 / ApplicationsAssembly work, by feel

Where touch decides.

Six assembly tasks where automation depends on what fingers feel, from wire harness assembly to control cabinet wiring.

Gloved hand pressing a cable into a clip on a wire harness board

A.01

Cable harness assembly

Routing, clipping and taping flexible cables, where grip force and feel matter more than sight.

Thumb and index finger mating a board connector

A.02

Connector mating

The push, the click, the check. The moment of success lives in a force signal, not in pixels.

Hand inserting a stripped wire into a terminal block in a control cabinet

A.03

Control cabinet wiring

Stripping, inserting and fastening wires in tight spaces, with precise finger control.

Fingertips inserting a two-lead component into a circuit board

A.04

Electronics assembly

Inserting components, fitting clips, handling delicate parts without damage.

Hand pressing a trim clip into a car door panel

A.05

Automotive final assembly

Clips, hoses and trim, fitted by feel inside cramped vehicle interiors.

Hand retrying a misaligned connector

A.06

Failure and recovery

Missed clicks, stuck parts, second attempts. The data robots need to fail safely and try again.

04 / What we captureTime-aligned

One synchronized record of skilled work.

  • 01Tactile and force signals at the fingertips
  • 02Full hand and finger pose
  • 03First-person and wrist video
  • 04Action labels, time-aligned and quality-checked

Delivered in standard formats for robot learning.

Record / Connector mating4 tracks
Force
Pose
Video
Labels
reachgraspinsertseatrelease
05 / How it worksThree steps

From skilled hands to robot hands.

  1. 01

    We partner with manufacturers.

    Skilled workers volunteer to wear our capture kit during normal production.

  2. 02

    We capture real work.

    Every task is recorded with touch, motion and vision, without slowing the line.

  3. 03

    We deliver train-ready datasets.

    Quality-checked, documented and licensed to robot makers and model teams.

06 / For manufacturersPartner plants

Turn your team's skill into value.

We are onboarding our first partner plants in Europe and Latin America. Partners receive a share of the value their data creates, their own copy of the data, and an automation study for their line.

Become a partner plant
07 / TrustConsent first

Built in Europe, built on consent.

  • T.01European data controller
  • T.02Voluntary participation, with opt-out at any time
  • T.03No performance monitoring of workers
  • T.04Documentation designed for EU AI Act data governance (Article 10)
08 / FAQ4 entries

Frequently asked.

Q.01Do you build robots?

No. We are independent and supply data to robot makers and model teams.

Q.02Can we commission specific tasks?

Yes. We scope capture programs around your tasks and your hardware.

Q.03Is the data exclusive?

We license data. Exclusivity windows are available.

Q.04Does participation affect worker evaluation?

No. Data is never used to assess individual performance.

09 / ContactBuyers and partner plants