DentalMonitoring raises €84M to scale AI orthodontics

DentalMonitoring secures €84M to scale AI orthodontic monitoring worldwide

Paris-based DentalMonitoring has raised a combined €84 million (about $100 million) from new investors to accelerate global expansion and further develop its AI-powered remote orthodontic monitoring platform.

A funding round shaped by “care outside the clinic”

The latest investment brings fresh capital into a category that sits at the intersection of medical devices, clinical workflow software, and consumer-friendly mobile health: orthodontic monitoring that can happen largely beyond the chair. The company describes its product as AI-powered software-as-a-medical-device (SaMD) designed to help dental professionals supervise orthodontic treatment remotely, with an emphasis on clinical oversight even when patients are not physically in the practice.

The round includes participation from Lazard Elaia Capital and ISALT (via ISALT’s Fonds Stratégique des Transitions), with the stated goal of funding international expansion and continued product innovation. In practical terms, this type of financing is often a signal that investors believe the platform can expand not just through sales growth, but through deeper integration with the broader dental ecosystem—manufacturers, scanners, and practice software—so that adoption becomes easier and outcomes become more measurable.

In conversations across healthcare, the phrase “remote monitoring” can sound like a convenience feature; in orthodontics, it can also be framed as a new operational baseline. Dental care is still inherently hands-on, but many check-ins are informational: Is the treatment progressing as expected, is there an issue that needs intervention, is the patient complying with instructions, and do they need an in-person appointment sooner than planned. A monitoring layer that triages these questions efficiently can reduce unnecessary visits while catching genuine problems earlier—benefits that matter to clinicians, patients, and healthcare systems that are increasingly cost-conscious.

This is also where the story connects to the broader AI-for-healthcare narrative that the ai world organisation tracks closely: successful AI products are rarely “AI-only” wins; they win because they fit real workflows, reduce friction, and deliver measurable clinical value. That’s precisely the kind of applied innovation that tends to take center stage at the ai world summit, where practitioners, builders, and investors compare what’s working in production versus what’s still hype-driven experimentation. As the sector heads toward ai world summit 2025 and ai world summit 2026, this round is a useful example of how AI gets funded when it is tied to clear adoption paths and defensible product positioning.

What DentalMonitoring is building (and why orthodontics fits AI)

DentalMonitoring was founded in 2014 and has grown its customer base to more than 2 million patients, positioning itself around AI-enabled monitoring of orthodontic treatments at scale. The company highlights product capabilities and modules such as DM Insights, ScanAssist, and DentalMonitoring+, reflecting a product strategy that goes beyond a single feature and instead aims to support multiple parts of the clinical monitoring workflow.

Orthodontics is a particularly strong “fit” for AI-assisted monitoring for a few reasons. First, treatment journeys are long, involving many incremental adjustments and periodic assessments, which creates a steady need for check-ins. Second, a lot of the data is visual—images, scans, progression markers—making it a natural domain for computer vision and pattern recognition, provided the system is built and validated properly. Third, orthodontic care involves patient behavior (wearing aligners as instructed, maintaining oral hygiene, following guidance), and remote monitoring can improve adherence through feedback loops and timely intervention.

From the clinic’s perspective, there’s a constant balancing act between maintaining a high standard of clinical control and handling time-consuming, repetitive follow-ups. A remote monitoring layer can help in two ways: it can flag cases that truly need attention and it can streamline routine confirmations that everything is on track. The net effect is often described as “more capacity without cutting corners”—a goal nearly every healthcare practice shares, especially as staffing constraints and patient expectations continue to rise.

From a patient’s perspective, the value proposition is intuitive: fewer unnecessary trips, quicker guidance when something feels off, and a clearer sense that someone is watching progress rather than waiting for the next appointment. In orthodontics, where treatment is measured in months and often years, reducing uncertainty is not a small thing. Done well, it can improve satisfaction, reduce dropout risk, and help align patient actions with clinical goals.

This is also why the remote monitoring market is not just a “telehealth add-on.” In dentistry, the difference between a platform that is lightly adopted and one that becomes standard can come down to integrations, ease of use, and trust. That trust is built through regulatory posture, clinical validation, and consistent outcomes—not marketing promises.

Where the €84M will go: markets, R&D, and integrations

DentalMonitoring says the new capital will be used to reinforce its presence in core markets—Europe, the United States, Australia, and Japan—while also supporting expansion into newer regions such as Brazil, Turkey, Southeast Asia, and the Middle East. This market list matters because it signals a “dual-track” growth plan: deepen leadership where the company already competes at scale, and open new growth corridors where demand for digital health and dental modernization is rising quickly.

Alongside geographic expansion, the company also plans to keep investing in innovation, including through the recent launch of a software development centre intended to strengthen AI research and development capacity. That point is important because in regulated healthcare contexts, product differentiation is rarely a one-time achievement. Models need maintenance, interfaces evolve, new devices and scanners enter the ecosystem, and compliance requirements shift across geographies. A serious R&D footprint is not optional if the company wants to remain credible as it expands.

The company also emphasizes ecosystem integration—further expanding partnerships and technical link-ups across the orthodontic digital stack, including appliance manufacturers, practice management software providers, and intra-oral scanning companies. This is the “plumbing” of modern healthcare software: clinicians do not want ten disconnected systems, and they don’t want manual copying of data across tools. Integrations reduce friction, speed onboarding, and make the AI layer feel like a natural extension of the clinic rather than yet another dashboard.

Another element of the plan is expansion beyond orthodontics into additional dental applications, leveraging AI technology and proprietary data. That’s a familiar scaling pattern in healthtech: start with a domain where the workflow is clear and the value is concrete, then broaden into adjacent use cases once the platform and distribution are strong enough. The tricky part is doing it without diluting focus—especially when regulatory expectations and clinical evidence standards may differ by application.

In the broader European dental and adjacent healthtech space, the original report notes that funding activity in 2025–2026 has been relatively modest, pointing to an example of another dental-focused platform raising €850k. In that context, an €84 million raise stands out not only for its size, but because it suggests that investors see a rare combination: scale, product maturity, and a credible path to global adoption.

Trust, regulation, and defensibility in AI dental care

AI in healthcare lives or dies on trust—trust from clinicians, regulators, and patients. DentalMonitoring positions itself as AI-powered SaMD for remote orthodontic monitoring, which places it firmly in a category where validation, documentation, and compliance are central to sustainable growth. In a parallel release, the company is described as having FDA De Novo approval and MDR certification, as well as a large image library and a substantial patent portfolio.

Specifically, the press release describes DentalMonitoring as having a “unique library of two billion images” and “over 470 patents,” framing these assets as part of its defensibility and ability to deliver real-time treatment updates across orthodontic treatments. Whether one agrees with the “operating system” metaphor often used for platforms, the underlying idea is clear: data scale, regulatory posture, and integration breadth can create a moat that is difficult for smaller point solutions to replicate.

The same release also notes that this investment follows operational profitability achieved in 2025, and that the funds are intended to support international expansion and product innovation. Profitability matters here because healthcare buyers are cautious; they want vendors that will be around for the full lifecycle of long treatments, enterprise contracts, and compliance updates. A business that can point to disciplined scaling tends to win more confidence from large clinic groups, partners, and strategic ecosystem players.

From the investor perspective, comments attributed to Lazard Elaia Capital frame DentalMonitoring as building a category rather than a single feature, emphasizing the platform’s ability to scale globally with a treatment- and appliance-agnostic model. That point—agnostic to specific treatments or OEMs—can be strategically powerful in orthodontics, where clinics may work with different brands, different patient needs, and different clinical preferences.

In plain language: if the AI layer works across many workflows and devices, it becomes easier for clinics to standardize on it, and easier for partners to integrate without betting on a narrow slice of the market. That’s how healthtech platforms become infrastructure rather than optional tooling.

Why this matters now (and what AI World readers should watch)

This story is bigger than one funding round because it captures an important trend: AI in healthcare is increasingly being funded when it’s embedded in routine clinical practice and supported by ecosystem partnerships, not when it’s presented as a futuristic bolt-on. For founders, the message is to build around workflows and outcomes; for investors, the message is to look for durability—regulatory positioning, real-world adoption, and integration pathways; for clinicians, the message is that remote supervision tools are becoming more capable and more common.

For the ai world organisation audience, DentalMonitoring’s expansion roadmap is also a useful lens on where applied AI is heading geographically: mature markets remain critical for revenue and credibility, while growth markets may drive the next adoption wave as digital infrastructure improves and patient expectations shift. This is the kind of “AI meets real-world operations” narrative that fits naturally into the programming of the ai world summit, and it’s why ai world organisation events increasingly focus on practical deployment stories—where the hard parts are integration, compliance, and change management, not just model accuracy.

If you’re tracking AI adoption in regulated industries, keep an eye on three signals as DentalMonitoring scales: first, the depth of its integrations with scanners and practice software; second, the company’s ability to expand into new dental applications without compromising clinical rigor; and third, how it navigates local regulatory and clinical standards across diverse regions. These are often the true determinants of whether a health AI platform becomes the default layer for a workflow or remains a niche tool used by early adopters.

To stay close to these patterns—and meet the builders, clinicians, and investors shaping them—follow the ai world organisation events calendar and the ai conferences by ai world ecosystem around the ai world summit, including ai world summit 2025 and ai world summit 2026 programming as it evolves.