Gravis Robotics

Autonomy retrofit kit for excavators and earthmoving equipment

Gravis Robotics builds the Gravis RACK, a rooftop-mounted retrofit kit that adds LiDAR, cameras, and GNSS RTK sensing to existing excavators and wheel loaders, pairing with the Gravis Slate touchscreen so one operator can supervise machines performing trenching, grading, and material-handling tasks with reduced manual input.

~$27M total ($4.35M seed, March 2023 + $23M Series A, November 2025) raisedGrowth Stage

Founded 2022 · Deployed with Holcim, Taylor Woodrow, Morgan Sindall Construction, Boskalis, and HD Hyundai across 7 countries (UK, US, EU, LATAM, Asia); UK's first large-scale autonomous excavation trial with Taylor Woodrow at Manchester Airport

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WHY IT EXISTS

Why This Tool Exists

The Problem

Construction and quarry operators face a chronic shortage of skilled excavator operators, and manual earthmoving on repetitive trenching, grading, truck-loading, and material-handling tasks is labor-intensive, inconsistent, and exposes workers to hazards around moving heavy equipment.

The Solution

The Gravis RACK retrofit kit fuses LiDAR, HDR cameras, GNSS RTK, and hydraulic feedback with a learning-based control system so an operator can define a dig area on the Gravis Slate touchscreen and let the machine execute repetitive earthmoving tasks autonomously from the cab, from outside the cab, or via remote teleoperation, with obstacle and people detection for safety.

USAGE

How You Use It

Delivery Method

Hardware Retrofit KitTablet App (Gravis Slate)

Integrations

Develon (OEM)HD Hyundai (OEM/customer)Flannery (UK equipment rental)Kibag (Switzerland dealer partner)

Disciplines

Construction, Civil Engineering

Workflows

Coordination & Delivery

Project Phases

Construction Administration

Project Types

Infrastructure, Commercial, Industrial

TRANSPARENCY

Data Transparency

Exactly what this tool uses and how

Input

What it needs

Required:Compatible excavator or wheel loader, 10-100+ tons, electronically controllable via electro-hydraulic pilot valves, Dig area/task definition via Gravis Slate touchscreen

Optional:Site plan import, Predefined excavation path

Formats:Physical machine retrofit (LiDAR, camera, GNSS sensor kit), Site plan files

Output

What you get

Format:Autonomously executed earthmoving work plus machine telemetry

Fields:Completed trenching, grading, or material-handling output, Real-time 3D terrain scans, Obstacle and people detection alerts, Machine performance and task-efficiency data

Algorithm

How it works

Model:Proprietary learning-based control system combining LiDAR, camera, GNSS RTK, and hydraulic feedback (model architecture not publicly disclosed)

Accuracy:Claims up to 30% higher throughput on high-volume tasks like truck loading, trenching, and bulk excavation; no independently audited accuracy benchmark publicly available

Privacy

How your data is protected

Retention:Not publicly specified

Training:Not publicly specified (vendor states machines contribute to an internal knowledge base of digging behavior and ground types; unclear whether this uses customer site data for model training)

Compliance:General privacy policy published with a named EU/Swiss data protection contact, No SOC 2, ISO 27001, or GDPR-specific certification publicly disclosed

API

Integration

Endpoint:Contact vendor for API access

Method:Not publicly documented

USE CASES

Use Cases

·Autonomous trenching and bulk excavation on active construction sites
·Automated truck loading and material handling at quarries and aggregates sites
·Grading and site preparation for infrastructure and airport projects
·Remote teleoperation of excavators from off-site locations
·Retrofitting mixed-brand fleets with autonomy instead of purchasing new autonomous machines

PRICING

Pricing

Free

Not publicly specified; no free tier, pilot programs offered to qualified customers

Pro

Available via equipment rental (e.g., through Flannery in the UK) or direct retrofit purchase/installation through dealers; pricing not publicly disclosed

Enterprise

Custom OEM and dealer partnership agreements (e.g., Develon, HD Hyundai, Kibag); contact vendor for pricing

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Research Sources & Data QualityLast verified: 2026-07-17

Data Sources (11)

Verified Data (14)

problem, solution, deliveryMethod, disciplines, projectPhases, projectTypes, maturityStage, yearFounded (2022, ETH Zurich spinout), customerBase, fundingTotal (seed + Series A), technology approach (sensor fusion, autonomy modes), useCases, control features, founders (Ryan Luke Johns, Dominic Jud, Marco Tranzatto, Burak Cizmeci)

Not Found (6)

api-documentation, exact pricing figures, soc2-or-iso27001-certification, data-retention-policy, ai-training-data-practices, independently-audited-accuracy-benchmarks

Our Commitment: We only include verified data from official sources. If information isn't publicly available, we mark it as "Not publicly specified" rather than guessing.

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