3DAI
3DAI turns vehicles already driving a road network into survey sensors: onboard cameras capture the road, and AI returns georeferenced data on surface defects and roadside assets for maintenance planning, inspection and asset inventory.
What is 3DAI?
3DAI is the road and asset intelligence platform built by Univrses AB, a Swedish computer vision company based in Stockholm. Its central idea is deceptively simple: rather than sending specialised survey vehicles onto the network, 3DAI turns vehicles that already drive it into sensors. Cameras mounted on those vehicles record the road and its surroundings during ordinary journeys, and AI converts the footage into structured, georeferenced data on surface condition and roadside assets. Every journey becomes a survey opportunity, and no road closure is required.
The platform is organised around three modules. Road Condition detects and classifies surface distresses — potholes, cracking, alligator cracking, rutting, ravelling, patching, deformation and unevenness — then reconstructs each one in three dimensions and places it at its real-world location instead of merely highlighting it on an image. Road Assets builds and maintains an inventory of roadside infrastructure: traffic signs across hundreds of classes, road markings, barriers, streetlights, manholes, drainage elements and works zones, each assessed for both position and visible condition. Road Inspection lets teams inspect remotely from the imagery, compare a location across successive passes, and assemble curated collections by asset, defect, route, project or maintenance area.
Accuracy claims are specific: sub-metre positioning for traffic signs in nominal conditions, and vision-based positioning described as up to 16 times more accurate than traditional GPS. Outputs include the pavement management indices road authorities already work with — PCI, IRI and RMS3 — so results feed existing budgeting and planning cycles rather than replacing them. New imagery is typically available within the same week, often the same day, and Univrses presents 3DAI as backwards compatible with historical survey datasets and existing asset management workflows.
Data reaches users through a web application or an API, and exports into GIS, pavement management and digital twin environments. On demand, imagery can be combined with connected-vehicle signals and Pirelli Cyber Tyre smart-tyre data. Privacy is handled upstream: faces and registration plates are blurred automatically, no personal data is stored, and Univrses states that all data is held within the EU. The platform is deployed in more than 15 countries alongside national road authorities, municipalities and maintenance contractors.
What it does
- Detect potholes, cracking, deformation and unevenness automatically across the network
- Reconstruct each defect in 3D and place it at its real-world location, not just on an image
- Build and maintain a roadside asset inventory: signs, markings, barriers, streetlights, drainage
- Rank defects by severity, urgency and change over time, linked to the relevant road segment
- Produce pavement management indices such as PCI, IRI and RMS3 for budgeting and planning
- Inspect remotely from imagery instead of travelling to site, and compare a location over time
- Export structured, georeferenced findings into existing GIS and asset management systems
When to use 3DAI / When not to
A quick filter to help you decide if 3DAI is the right fit.
When to use 3DAI
- National road authorities running network-wide condition monitoring, such as the transport administrations Univrses names among its references
- Municipal and urban maintenance teams that need street-level condition data without commissioning a dedicated survey
- Term maintenance contractors who must evidence completed work, track SLA performance and strengthen tender submissions
- Highway owners and infrastructure operators whose asset inventory is missing, outdated or held in spreadsheets
- Public-sector buyers who need road imagery processed under a GDPR-compliant, EU-hosted arrangement
When not to use 3DAI
- Anyone needing real-time road monitoring: the data is survey-based and refreshed pass by pass, not streamed live
- Small operators without a fleet of vehicles already circulating on the network to be measured
- Buyers who want to compare published prices or self-serve, since every engagement starts with a sales conversation
- Teams looking to inspect bridges, tunnels or buildings, as the scope described is the road surface and its immediate roadside
- Individuals or mobile-first users, because there is no iOS or Android application and no consumer offering
How to use 3DAI
A typical end-to-end flow, from setup to results.
- Request a demonstration or a tailored proposal through the Get Started page — there is no self-service sign-up
- Agree the scope with Univrses: network size and coverage, which monitoring capabilities you need, and collection frequency
- Take out an annual subscription for a first capability, such as road condition monitoring or asset inventory
- Fit Univrses cameras to connected vehicles that already travel the network, with no dedicated survey run to schedule
- Let data be captured during normal operations, with no road closures and no change to existing driving patterns
- Watch coverage build up automatically as vehicles repeatedly cover the same roads and observations are aggregated
- Open the web application to review detected defects and assets, ranked by severity, urgency and evolution
- Save key locations, label images and group them into collections by asset, defect, route, project or maintenance area
- Pull imagery and structured data through the API and export them into your GIS, pavement or asset management systems
- Extend the subscription over time to further capabilities, such as roadside asset inspection or resilience monitoring
Pros & Cons
Pros
- Removes the dedicated survey fleet: capture happens during journeys the network already sees, with zero road closures
- Refresh rate far beyond an annual survey — new imagery is typically available within the week, often the same day
- Defects are reconstructed in 3D and geolocated, rather than simply highlighted on a photograph
- Outputs use standard pavement indices and export into existing systems, so it augments rather than replaces the toolchain
- Privacy is engineered upstream — automatic blurring of faces and plates, no personal data stored, EU data residency
- Verifiable public references with national road authorities and cities across more than 15 countries
- Published customer outcomes are concrete: 8,800 km covered, 95% classification accuracy, 110,000 streetlights classified in 90 days
Cons
- No price is published at all — no figures, no tiers, no indicative range — so budgeting requires a sales conversation
- No free plan and no free trial is advertised: there is no way to evaluate the platform independently
- The site publishes no terms and conditions and no legal notice, so the contract is invisible before commercial contact
- No data processing agreement is published or mentioned, and no subprocessor list is available
- The API is sold as an access route but has no public documentation: scope, quotas and formats are unknown in advance
- Retention is never quantified — only no longer than necessary and erasure on a regular basis
- The data is survey-based rather than real-time, and requires a fleet already covering the network you want measured
Pricing & Plans
No free plan and no free trial are advertised, and no price is published anywhere on the site, so there is no lowest price point to report in any currency. Univrses sells 3DAI as a subscription: plans start with annual subscriptions for individual capabilities, such as road condition monitoring or asset inventories, and can be extended to cover roadside asset inspections or infrastructure resilience monitoring. The amount quoted is stated to depend on five factors: the size and coverage of the road network, the monitoring capabilities selected, how frequently data is collected, integration and reporting needs, and the level of technical and professional support required. Every subscription is said to include continuous access to road and infrastructure data, regular updates as new data is collected, new platform capabilities on release, deployment across networks of any size, integration with existing GIS, asset management and digital twin environments, and expert support from the Univrses team. Pricing is obtained by requesting a tailored proposal.
Data, GDPR & hosting
A consolidated view of how 3DAI handles your data.
GDPR overview
GDPR compliance is claimed explicitly and repeatedly, on the product pages and on a dedicated Privacy & Security page. The privacy policy cites Regulation (EU) 2016/679 by name and enumerates data subject rights: information, access, a free copy of stored data, rectification, erasure, objection to direct marketing including profiling analysis, restriction of processing and portability. Objections to direct marketing are directed to personaldata@univrses.com. Univrses reserves the right to refuse or charge a reasonable fee for manifestly unfounded or excessive requests, and names Datainspektionen as the supervisory authority for complaints. Anonymisation is presented as the central control: faces and registration plates are blurred beyond reasonable recognition and Univrses states it will not attempt to identify anyone appearing in its data. As an EU-established company, no Article 27 representative applies. The policy carries no effective date and no version number.
Who owns the data?
Univrses states that clients keep control of their data: the platform enables internal use across a client's departments, but Univrses says it never merges or shares data independently and that every process is designed to keep ownership clear. Selling or sharing personal data is explicitly excluded from its business model. Beyond those statements, ownership is not documented publicly. The site publishes no terms and conditions and no data processing agreement, and its privacy policy covers only Public Environment Personal Data — the incidental footage of people and number plates captured in public space — rather than the imagery, asset inventories and condition histories produced for a paying client. Ownership of that material is therefore a matter for the contract.
Reuse rights
No published terms grant or restrict reuse, because Univrses publishes no terms and conditions: what a client may do with its 3DAI outputs is settled contractually rather than on the website. What the site does describe is practical reuse. Structured, geolocated data exports directly into existing pavement and asset management systems; images can be accessed and downloaded through the web application or the API; and curated collections can be shared across teams, departments and contractors. Univrses' own reuse of captured material is stated separately: the privacy policy says imagery may be captured in connection with the development of its computer vision and machine learning software, while faces and registration plates are blurred automatically.
Data retention & training
Hosting summary
Univrses states that all data is stored securely within the EU, and repeats the claim as within Europe on its Privacy & Security page. No hosting country is named, no cloud provider is identified and no subprocessor list is published, so the jurisdiction is asserted at regional level only. One distinction matters when reading the site: the frequent Built in Sweden and Developed in Sweden statements describe where the software is engineered, not where customer data resides, and the two should not be conflated. Univrses frames EU residency as part of a wider positioning, presenting itself as a Swedish AI company building to European values of transparency, accountability and respect for privacy, and stating that systems are designed to minimise exposure at every step. For a public-sector buyer this is a workable starting point rather than a complete answer: the specific country, the infrastructure provider and the full processing chain all remain to be established in contract, alongside the data processing agreement the site does not publish.
Things to keep in mind
Risks and trade-offs to weigh before adopting 3DAI.
- No terms and conditions or legal notice are published, so the contractual framework cannot be reviewed before engaging commercially
- No data processing agreement is offered publicly, although the tool processes public-road imagery on behalf of public bodies — request one explicitly
- No subprocessor list is published, so the processing chain cannot be verified from the outside
- Retention is undefined, and nothing is said about how long the client's own anonymised imagery and asset histories are kept
- The claim we never train on personal data does not address non-personal client data, while the privacy policy says captured imagery serves software development — clarify this in contract
- Continuous condition data can invite over-reliance on automated severity ranking: engineering judgement and on-site verification still decide what actually gets repaired
- Customer logos span both product lines and include automotive partners, and headline metrics come from specific deployments rather than being contractual guarantees
Setup & Integrations
Technical difficulty
Low for the end user, moderate at programme level. Univrses describes setup as collecting data with its cameras on connected vehicles: there is no survey run to schedule and no road closure. Daily use needs no installation, since the platform is a web application, with an API for integration. The real effort sits upstream — fitting cameras to vehicles that already cover the network, and wiring exports into existing GIS and asset management systems. Univrses claims backwards compatibility with historical survey datasets and includes expert support in every subscription, but publishes no technical documentation, so integration is scoped with the vendor.
Deployment
Integrations
Supported languages
Behind 3DAI
Social
Resources
All the official URLs gathered for verification and reference.
Frequently asked questions
Does 3DAI require a dedicated survey fleet?
How often is the data updated?
What does 3DAI actually detect?
Which pavement management indices does it produce?
How much does 3DAI cost?
Is there a free trial or a free plan?
How do users access the data?
How is privacy handled?
Where is the data hosted?
Who is behind 3DAI?
Should you pick 3DAI?
3DAI is a mature product resting on an unusually solid foundation: a decade of automotive computer vision at Univrses, redirected toward public infrastructure in 2022. The value proposition is essentially economic. Road surveying has always been expensive because it required specialised vehicles and dedicated runs; 3DAI makes the survey a by-product of journeys the network already sees. That single change is what turns an annual snapshot into something close to continuous coverage, and it explains why the reference list is credible — national transport administrations, large maintenance contractors and cities across more than 15 countries, all named and independently checkable.
For a European public buyer the compliance story is also unusually legible. Anonymisation happens upstream rather than as a promise, the vendor is EU-established, and data residency is asserted within the EU. Outputs land in the indices road engineers already use, which matters more than it sounds: the platform augments the existing toolchain instead of asking an authority to abandon it.
The reservations are commercial and contractual rather than technical. Univrses publishes no price, no terms and conditions, no legal notice, no data processing agreement and no subprocessor list, and it markets an API for which no documentation exists publicly. Its privacy policy is genuinely detailed, but it addresses incidental footage of the public, not the ownership or retention of the client's own imagery and asset histories. None of this is unusual for enterprise infrastructure software sold through tenders, and none of it is a defect in the product — but it does mean the entire commercial and legal envelope has to be constructed in negotiation. Buyers should arrive with their DPA, their retention schedule and their API questions already written.
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