Looq AI

What is Looq AI?

Looq AI is a spatial AI platform that builds georeferenced 3D models of infrastructure from photos taken at ground level. Instead of flying a drone or setting up a laser scanner, a surveyor walks the site carrying the qCam, a handheld camera unit with satellite positioning built in.

The workflow has three parts. The qCam records wide-angle imagery alongside GNSS and inertial data, the qAI cloud engine turns those images into a classified point cloud, and the qApp web viewer lets project teams measure, inspect and export the results. Because the heavy processing happens online, the field kit stays small and the office does not need a high-end workstation to build the model.

Looq AI is based in San Diego and was founded in 2021 by Dominique Meyer, its chief executive, and Shreyas Niradi, its chief technology officer. In 2026 it received a Constructech Top Products Award and a DTECH Power Players Award. Funding reports say it has raised $3.75 million. The company sells mainly to survey firms, engineering consultancies and utilities, and its website was still accepting demo requests in early October 2026.

Key Features

Ground-level photogrammetry with satellite positioning drives the whole product: one handheld camera feeds a cloud engine that outputs measured, labelled 3D data. The six capabilities below explain how that chain works in practice.

• qCam capture unit: The qCam combines a wide-angle camera with a GNSS receiver and an inertial measurement unit in one handheld device. Each photo is therefore tagged with position and orientation as you walk, which removes much of the manual control work photogrammetry usually needs.
• qAI cloud processing: Uploaded imagery is processed by qAI, which builds dense point clouds without any LiDAR sensor. Moving the computation to the cloud means field teams can start the next job while the model is being built elsewhere.
• Automatic feature labelling: Looq says qAI recognises and tags more than 200 attribute types, including utility poles and overhead wires. Labelled assets save drafting time, because engineers can filter the cloud by object type rather than tracing every feature by hand.
• PPK positioning accuracy: Post-processed kinematic positioning targets roughly 3 cm horizontal and 6 cm vertical accuracy on standard jobs. Looq states that a local base station tightens this further, and that aligning to ground control can bring results under 1 cm.
• qApp browser viewer: The qApp viewer opens projects in a web browser for measuring distances, checking clearances and reviewing captured imagery. Clients and colleagues can inspect a site without installing desktop point-cloud software or downloading very large files.
• Automatic privacy blurring: Faces and vehicle number plates in captured imagery are blurred automatically during processing. This matters for street and corridor surveys, where crews inevitably photograph members of the public and parked cars.

Pros

Light field kit is the strongest argument for Looq AI, since a single walking camera replaces the drones and tripod scanners that usually slow small surveys down.

• No drone or scanner needed: One handheld device does the capture, so there are no flight permissions, batteries for multiple aircraft or scanner setups. Crews working under bridges, along streets or in restricted airspace gain the most.
• Quick time on site: A customer case on the Looq site describes capturing a bridge in under ten minutes. Shorter visits cut traffic management costs and reduce the time surveyors spend near live roads.
• Outputs fit existing tools: LAZ, GeoTIFF, DXF, SHP and CSV exports load into the CAD and GIS packages most firms already own. Teams can adopt Looq without retraining drafters on new design software.
• Clear data ownership: Looq says data is encrypted in transit and at rest from the moment of capture, and that customers keep ownership. Utilities handling sensitive network records will find this stance easier to approve internally.
• Labelled assets save drafting: Automatic tagging of poles, wires and similar features gives engineers a head start on asset registers. Line clearance checks and inventory work begin from classified data rather than a raw, unsorted point cloud.

Cons

Closed pricing is the main obstacle with Looq AI, because hardware, processing and viewer costs are only revealed after a sales demo.

• No published prices: Looq lists no plan or per-project figures on its website, and we found none in directories either. Smaller firms cannot compare it against scanners or drone kits without first booking a sales call.
• Tied to its own hardware: The workflow depends on the qCam, so photos from your existing cameras or phones are not the intended input. That adds an equipment commitment before you can judge results on your own projects.
• Little independent feedback: When we checked, the G2 listing showed no user reviews, and independent accuracy tests are scarce. Most evidence comes from the vendor and its customers, so a pilot project is the safest check.
• No named security audits: The Looq trust centre describes encryption but does not list SOC 2 or ISO 27001 certification. Public-sector and utility buyers with strict procurement rules may need extra assurances in writing.
• Vertical accuracy trails horizontal: Standard processing targets about 6 cm vertically, double the horizontal figure. Jobs needing tight levels, such as drainage design, will likely require a base station or ground control.

Who is Using Looq AI?

Survey and infrastructure professionals form Looq AI’s customer base, mostly teams that map long corridors or many assets and want to spend less time on site. Customers quoted on its homepage include AJ Surveying and Aquawolf.

• Land surveyors: Survey firms capture bridges, road corridors and street scenes on foot. They deliver point clouds and orthophotos to clients in standard formats.
• Civil engineers: Design consultancies record existing site conditions before drafting. DXF and LAZ outputs feed straight into Civil 3D and similar packages.
• Transmission and distribution engineers: Specialists model poles, conductors and clearances along power lines. Automatic labelling of wires and poles shortens their inspection reviews, and the early-access qPole workflow targets pole loading analysis.
• Utility asset managers: Network owners build and refresh asset inventories across large service areas. Shapefile and CSV exports slot into ArcGIS-based asset records.

Pricing

Looq AI publishes no prices and asks every buyer to book a demo for a quote (official site, checked October 2026). Expect a package that bundles the camera hardware with cloud processing and viewer access.

Directory listings and funding coverage gave no figures either, so treat any number quoted elsewhere with caution. Sales can be reached by phone or at [email protected] on weekdays from 9am to 5pm Pacific time.

Disclaimer: hardware and subscription quotes can differ by region, project volume and contract length, so ask for a written breakdown before committing.

What Makes Looq AI Unique?

Looq AI pairs a walking camera with cloud AI, which lets one person produce survey-grade 3D data without LiDAR, drones or tripod setups. Most reality capture tools ask you to choose between expensive laser scanners and drone photogrammetry that needs open sky and flight approval.

Ground-level capture also reaches places drones struggle with, such as the underside of bridges, tree-lined streets and busy urban corridors. Adding automatic asset labelling on top turns raw imagery into a classified inventory, which is where utility and transport clients see the most value. In February 2026 Looq announced qPole, an early-access workflow that it says captures a pole in about two minutes and cuts modelling time from roughly 30 minutes to under 13.

Compatibilities and Integrations

Looq AI exports open survey formats that load into Civil 3D, Trimble Business Center, TopoDOT and Esri ArcGIS, so it slots into existing CAD and GIS workflows.

• Platforms: The qCam handles field capture, while the qApp viewer runs in a standard web browser.
• CAD and survey software: Autodesk Civil 3D, Trimble Business Center and TopoDOT for drafting and extraction, plus SPIDACalc, PLS-CADD and O-Calc for pole models from qPole.
• GIS: Esri ArcGIS for asset records and mapping.
• Data formats: LAZ point clouds, GeoTIFF orthophotos, DXF, SHP, CSV, XML metadata and panoramic JPG images.

Looq AI Tutorials

A Looq AI project follows a short loop of capture, upload, review and export once your account and hardware are in place.

1. Book a demo with Looq and agree a hardware and processing package.
2. Set up the qCam outdoors and wait for a stable GNSS fix before walking.
3. Walk the site at a steady pace, keeping the assets you need in view.
4. Add a local base station or ground control points if the job needs tighter accuracy.
5. Upload the capture to qAI and wait for the classified point cloud.
6. Measure and review in qApp, then export LAZ, DXF or SHP files to your design software.

How We Rated It

Looq AI earns 3.9 out of 5: centimetre-level positioning and strong CAD and GIS exports score well, while hidden pricing and thin public support pull it down.

Summary

Looq AI suits survey firms, engineering consultancies and utilities that want georeferenced 3D site data without flying drones or hauling laser scanners. Its handheld capture, automatic asset labelling and standard exports make it a practical fit for corridor and network work. The main drawback is closed pricing, combined with very few independent reviews or published audits. Before signing, ask for a pilot on one of your own sites and compare the results against control points you already trust.