The bridge between clinical need and deployed AI.
Clinical AI rarely fails in the model. It fails in the space between clinical need, data, validation, workflow, and decision impact. We research and develop custom health AI models and systems, and we work across that entire chain, from first concept to deployed, validated solution.
Deep expertise on both sides of the bridge.
- Health data, end to end: medical images, wearables, smartphone sensing, electronic health records (EHRs), and audio.
- The full AI toolkit: traditional machine learning, deep learning, and large language models (LLMs), applied where each fits best.
- $50M+ in funded AI research from NIH, NSF, DARPA, Google, and NVIDIA.
- 200+ peer-reviewed publications in top AI-for-health journals and conferences.
- Multiple patents and provisional patents in AI for healthcare.
- Co-founders of multiple AI health tech startups. We know what it takes to move research into products.
- Multidisciplinary by design: experienced collaborating across the teams of AI experts, clinicians, and patient populations that health AI demands.
- Breadth across conditions: mental health, infectious disease, cardiology, wounds, and traumatic brain injury, among others.
25 years of award-winning research, and real deployed systems.
For 25 years, our team has led a top academic AI-for-health lab: research funded by NIH and DARPA, published in peer-reviewed venues, and covered by the Boston Globe, the BBC, Wired, and the Financial Times. Multiple projects have been spun out into startups. When you work with Concordance, you work with that same team, across the full lifespan of your AI health project.
Evidence over benchmarks.
Our AI, measured against clinicians.
Our deep learning wound infection model was evaluated head-to-head against healthcare professionals. The work was nominated for Best Paper at the American Association of Plastic Surgeons' 2025 Annual Meeting.
Our systems reach real users.
We have built and deployed health sensing apps used by thousands of people, and clinical decision-support tools evaluated with physicians, nurses, and patients.
Our methods are validated the hard way.
Clinical studies with hospital partners. Subgroup and fairness evaluation across patient populations. Peer review at top venues including NeurIPS, AAAI, and IEEE journals.
A structured path from first assessment to deployed solution.
Discovery
Is AI right for your problem, and what is the best solution direction?
Roadmap
A concrete, milestoned development plan.
Build
A working, validated model built from your data.
Integrate
Embedded into your product, with ongoing applied research support.
Start with a Discovery engagement.
A focused, fixed-fee assessment of whether AI is right for your problem, and what the best solution looks like.