Sixth Sense Robotics

AI decision layer for robots

The judgment layer for every robot.

Sixth Sense sits on top of your robots. It decides what to do with every item, acts when its confidence is high, asks an operator when it is not, and records each decision.

Live decision feed Threshold 85%
  1. Item: Vial batch 2231

    Action: Route to line B

    96%
    State: Acted
  2. Item: Carton, torn seal

    Action: Hold for check

    72%
    State: Asked operator
  3. Item: Tray 18, 12 units

    Action: Pick and place

    93%
    State: Acted
  4. Item: Unlabelled bag

    Action: Stop conveyor

    41%
    State: Blocked
  5. Item: Sample kit 0417

    Action: Pass to packing

    98%
    State: Acted
  6. Item: Crate, new supplier

    Action: Hold for check

    79%
    State: Asked operator

Illustrative example. Not live data.

The problem

Robots are affordable. Exceptions are not.

A robot arm costs less than a car. Yet most of them stop at the first item that does not match the script: a torn label, a new packaging, a product that arrived a day early.

Every new product, every new rule, means another round of reprogramming. The integrator is booked, the line waits, and the business case slips.

Palletizing robot placing cardboard boxes on a conveyor
  • Stops at the first exception

    Anything outside the programmed cases halts the line or needs a person to step in.

  • Every change is a project

    New products and new rules go back to the integrator for reprogramming.

  • No record of why

    When something goes wrong, nobody can show what the robot saw and why it acted.

How it works

Perceive, decide, act or ask, record.

Four steps, on every item, every time. The same loop runs on any robot brand and on any model you choose.

  1. 01

    Perceive

    Camera and sensor data become structured facts about the scene: what the item is, its state, where it sits.

  2. 02

    Decide

    The model picks an action and attaches a confidence score to it.

  3. 03

    Act or ask

    Above the threshold the robot acts. Below it, an operator gets the case on a tablet and decides.

  4. 04

    Record

    Every decision is logged with its confidence, the action taken and who approved it.

Confidence meter

Each decision carries a score. You set the threshold per task. Above it the robot acts, below it a person is asked. Move the threshold and watch the outcomes change.

Below 50 percent the action is blocked whatever the threshold.

Confidence meter Threshold 85%
  • Vial batch 2231 Acted
    96%
  • Sample kit 0417 Acted
    89%
  • Carton, torn seal Asked operator
    72%
  • Crate, new supplier Asked operator
    58%
  • Unlabelled bag Blocked
    41%

Acted: 2 · Asked operator: 2 · Blocked: 1

Illustrative example. In production the threshold is set per task, and a safety rule can block any action whatever the score.

Product demo

See it decide.

Two minutes in a simulated pharma cell. Routine boxes flow, a crushed box is blocked, an operator answers on a tablet, a rule changes in plain words, and every decision lands in the audit log.

Simulated cell with generated items. The console, the rules and the log are the real software. 2:07

What happens in the video

  1. A robot sorts pharma boxes. Every item gets a decision and a confidence score. Above the threshold, it acts on its own.
  2. A crushed box arrives. A hard safety rule blocks it. The AI cannot override it.
  3. A label is unreadable. The robot is not sure, so it asks. The operator decides on a tablet, choosing only among safe options.
  4. A new rule is written in plain words. The console shows conflicts and impact before anything changes. Once confirmed, the next expiring box goes straight to reject.
  5. Every decision is recorded: what it saw, why it acted, who approved. Everything runs on premise.

The operator console

  • Live view of the console: arm state, current item, candidate actions and decision feed

    Live

    The arm state, the current item with its facts, the candidate actions with their probabilities, and the decision feed.

  • Escalation screen asking the operator to decide on a crushed box, with locked options

    Escalations

    The question to the operator: image, reason and only the actions the rules allow. Options locked by a hard rule stay disabled.

  • Rules screen with a proposed rule, its conflicts and an impact preview

    Rules

    A sentence becomes a structured rule. Priority, overlaps with existing rules and the impact on recent items are shown before confirmation.

  • Audit log table with a decision record open on the side

    Audit

    One record per decision: timing, gate outcome, rules fired, model version and who approved.

Technology

Fast decisions, hard limits.

Sixth Sense uses a new class of AI decision models. They do not write text: they choose between the actions the rules allow and return a calibrated probability for each, in a fraction of a second.

Deployment

  • On premise compute (Apple Silicon or NVIDIA)
  • Existing cameras
  • Robot controller integration
  • Tablet console
  • Audit export (CSV/JSON)
  • ROS 2 integration Roadmap
  • Additional robot brands Roadmap
  • Fleet dashboard Roadmap
Architecture How a decision travels from the camera to the robot.
Architecture Cameras and sensors feed the perception module, which turns the scene into structured facts. The rule engine takes those facts and produces the list of allowed actions. Hard safety rules are applied here, in deterministic code. The decision model picks one of the allowed actions and returns a confidence for it. The confidence gate compares that confidence with the threshold set for the task. Above the threshold, the robot controller runs the action. Below the threshold, the case goes to the operator console on a tablet. The operator decides, and the controller runs that decision. Every step writes to the audit log. Cameras and sensors Your existing hardware Perception Scene to structured facts Rule engine Allowed actions, hard limits Decision model One choice, with confidence Confidence gate Threshold set per task Operator console Tablet, one tap to decide Robot controller Runs the action Audit log Every decision recorded Below threshold Operator decision Every step Above threshold
Read the diagram as text
  1. Cameras and sensors feed the perception module, which turns the scene into structured facts.
  2. The rule engine takes those facts and produces the list of allowed actions. Hard safety rules are applied here, in deterministic code.
  3. The decision model picks one of the allowed actions and returns a confidence for it.
  4. The confidence gate compares that confidence with the threshold set for the task.
  5. Above the threshold, the robot controller runs the action.
  6. Below the threshold, the case goes to the operator console on a tablet. The operator decides, and the controller runs that decision.
  7. Every step writes to the audit log.

The model

System One models

Sixth Sense runs on System One models, a new generation of AI models built for one job: choosing. The name comes from the fast, intuitive mode of human thinking, the one that recognises a situation and acts on it without deliberating in words.

A System One model takes the structured facts from perception and the list of actions the rules allow. It returns one choice and a calibrated confidence for it. It does not generate text, plan or reason step by step, and it never proposes an action outside the list.

Because the output is a probability, not a sentence, it can be measured, thresholded and audited. Below the threshold the model does not act at all. A person does.

Chooses, does not write
The output is one action from the allowed list and a confidence score. No free text.
Calibrated confidence
A score of 90 percent should be right about nine times in ten. We check that against your decision log.
Small and fast
Answers in a fraction of a second on a small box on site. No data centre needed.
Swappable
Any model that returns a choice and a confidence can take its place. Sixth Sense is not tied to one vendor.
  • Safety lives in code

    Hard rules are deterministic code. The model can never override them.

  • The model only chooses

    It picks from the actions the rules allow. It never invents new ones.

  • On premise

    Runs on a small box on your site. No data leaves your network.

  • Swap anything

    Any decision model, any robot brand, any camera.

Plain language rules

Change the rules without reprogramming.

An operator types what should change. Sixth Sense turns it into a structured rule and waits for confirmation before it applies.

  • Rules are versioned. You can see who changed what and when.
  • A rule never applies before a person confirms it.
  • No code, no downtime, no ticket to the integrator.

Operator console

Illustrative example

New rule

From now on, anything expiring before March goes to reject

Structured rule

Condition
expiry_date < 1 March
Action
Reject
Scope
All items, all lines
Applies
From confirmation
Awaiting confirmation

Use cases

Where variety beats volume.

Sixth Sense fits work where items change often and every exception costs time.

  • Robot arm handling a sample plate in a laboratory

    Pharma and labs

    The problem
    Samples and vials vary by batch, and every handling step must be traceable.
    With Sixth Sense
    Sixth Sense checks each item, asks when unsure and keeps an audit trail for every decision.
    Read the use case
  • Robot arm handling storage crates in an automated warehouse

    Logistics and ecommerce

    The problem
    Thousands of SKUs, damaged parcels and new packaging arrive every day.
    With Sixth Sense
    The robot keeps picking on familiar items and routes the odd ones to an operator.
    Read the use case
  • Industrial robot arm working at a manufacturing station

    Manufacturing and packaging

    The problem
    Short runs and frequent changeovers make fixed programs expensive to maintain.
    With Sixth Sense
    Rules change in plain language, so a new product does not need a new program.
    Read the use case
  • Eggs moving along an automated sorting line

    Food and agriculture

    The problem
    Natural products differ in shape, ripeness and quality from one piece to the next.
    With Sixth Sense
    Grading and sorting decisions carry a confidence score, with people deciding the borderline cases.
    Read the use case
  • Delivery robot moving through a busy indoor corridor

    Healthcare and services

    The problem
    Robots meet people and unplanned situations in wards, kitchens and back offices.
    With Sixth Sense
    The robot stops or asks whenever the situation leaves the expected range, and logs why.
    Read the use case

Why Sixth Sense

Built for plants, not for demos.

  • On premise by design

    The whole stack runs on your site. Images, decisions and logs never leave your network.

  • Works with any robot

    Model agnostic and brand agnostic. It connects to the robots and cameras you already own.

  • Every decision auditable

    Confidence, action and approver are recorded for each item, ready for inspection.

  • Rules in plain language

    Operators change behaviour by writing what should happen. No reprogramming.

  • Humans stay in control

    You set the thresholds. Below them, a person decides. Above them, you can still review.

Who it is for

Made for the people who put robots to work.

  • System integrators and robot resellers

    Deliver cells that handle variety, and stop losing margin on every exception request.

  • Robot manufacturers entering Europe

    Add a decision layer that meets on premise data requirements and audit expectations.

  • Businesses with high variety and low volume

    Automate lines that were never worth a custom program.

FAQ

Questions we hear first.

Short answers. Where something is not fixed yet, we say so and define it per pilot.

Is it safe?

Safety rules are deterministic code, and the model can only pick from the actions those rules allow. Below the threshold nothing moves until a person decides. Guards, light curtains and emergency stops stay with the cell. Sixth Sense adds judgment; it does not replace safety hardware.

What data leaves our site?

None by default. The software runs on a box on your premises. Images, decisions and logs stay on your network. Remote support is off unless you switch it on, and its scope is defined per pilot.

Which robots does it work with?

Any robot whose controller accepts commands from an external system. The brands covered by a pilot are confirmed during scoping. ROS 2 support and more brands are on the roadmap.

How long does setup take?

It depends on camera access, controller access and the number of rules. Setup time is defined per pilot, and the pilot plan reserves its first days for it.

Does it replace our integrator?

No. Your integrator keeps the cell, the safety concept and the robot program. Sixth Sense adds the decision layer and works with your integrator. We also work with integrators directly.

How is it priced?

Pilot pricing is defined per pilot. Pricing after the pilot depends on the number of cells and is agreed before the pilot ends. There is no fee per decision.

Pilot program

We are selecting three pilot partners.

In pharma, labs and logistics. One cell, your items, your exceptions. At the end you keep the full decision log, whatever you decide next.

Apply for the pilot

What a pilot includes

  • One robot cell on your site
  • Your items and your real exceptions
  • Four weeks
  • The full decision log at the end

See it decide live.

Bring your items and your exceptions. We will show you what the robot does with them.

Book a demo