HLTH 2026 · Nov 15–18
Book a slot →We design, build and run production-grade data platforms and AI systems for medtech, diagnostics, healthcare providers and life sciences. Specialized in healthcare, built to pass regulatory and security reviews, and measured in business outcomes: cost saved, time saved, new revenue.
data and AI projects in healthcare and research: imaging, clinical NLP, data platforms, MLOps
Technical leaders with a model that isn't a system yet, business leaders who need a number, not another pilot, and providers and labs sitting on data nobody can use. The fix is usually faster than you think.
Healthtech and medtech. Training is ad hoc, data isn't versioned, there is no audit trail, and the submission date isn't moving. You need the platform around the algorithm.
Healthtech and medtech. Budget, a deadline, and a pilot nobody can defend in a board meeting. We start from the outcome: the metric, the owner, the definition of done.
Providers, labs and research teams. Imaging, device and EHR data live in silos; reports are assembled by hand; nothing repeats. A governed platform makes the next question cheap.
Most of our clients already have engineers. What they are short of is capacity, and experience in regulated environments: the data platform, the models, the MLOps that keeps them accurate and compliant, and the secure cloud they run on. Six services, in the order most teams need them. Start anywhere.
Training pipelines, data and model versioning, drift monitoring and an audit trail. FDA- and EU MDR-ready: data lineage, training records, validation and change control your regulatory team can rely on.
Pipelines that bring DICOM, HL7 FHIR, genomic and device data into one governed platform: cataloged, de-identified where needed, and accessible to the people who need it, from R&D to finance.
Landing zones, migrations and production infrastructure on your own cloud account: encryption, logging, access control, backups, cost control. AWS is our default and deepest expertise (AWS Select Partner); other clouds and on-prem when that is where you are.
Diagnostic models validated on your data, document understanding that pre-fills registry forms, voice agents that collect what matters, and AI agents with a human in the loop.
Consented patient data, de-identification, governance and labeling tooling with auditable access, so your ML team stops waiting for data.
Decision-ready reporting on governed foundations: integrated reporting across sites and systems, revenue cycle automation with a specialist in the loop, and data products with a number attached.
An hour, no commitment. Where you are, what you want to achieve, and whether we are the right fit. If we are, you leave with a Discovery Phase proposal sized to your project. Honest, even if the answer is no.
25+
production data and AI projects delivered in healthcare and research
$79M
acquisition our diagnostic AI directly contributed to
60%
less documentation time in a live hospital deployment (clinical NLP)
40%
more experiments in the same time on a genomics MLOps platform
Patient data deserves more than a demo. We design every pipeline and model with privacy, traceability and clinical safety built in from day one, on infrastructure you own.
Built to pass all 3:
Before any architecture, the Discovery Phase checks whether the system is worth building: the ROI, the data you actually have, the regulatory path. Sometimes the honest answer is: don't build it.
HIPAA, GDPR, FDA and EU MDR requirements are foundations, not a review at the end: secure, auditable and production-grade from the first sprint.
Code in your repositories, systems on your cloud account, documentation your engineers can act on without us. Every stage ends with something you keep.
Solutions are sketched and then led by experienced architects. Three people set the direction; specialists in the healthcare domain and in the technologies under it deliver. Short decision paths, direct access to seniors.
Former CTO with end-to-end technical ownership in three medical deep-tech startups, two of them later acquired (larger deal: USD 79M). At datarabbit he oversees the Discovery Phase and designs solution architectures with a focus on each project's impact and ROI.
Michał on LinkedIn
Radiologist with a PhD focused on AI in medicine; his research collaborations include leading labs worldwide, Stanford among them. Leads the clinical side of datarabbit's projects that involve clinical data or hospital workflows.
Assistant professor at Poznań University of Technology with a PhD in machine learning research. In the past he worked with supercomputing centers and drove technical work in EU R&D projects with combined budgets of over EUR 50M. At datarabbit he leads R&D, from model benchmarking to evaluation design.
A clear, de-risked path with a boundary at every stage: what you get, and what belongs to the next step. You can stop after any of them and keep everything produced so far.
An hour with one of our architects, sometimes a follow-up. No commitment. Where you are, what you want, and whether a Discovery Phase makes sense for you.
1h with an architectAn audit of what you have, or a plan for what you need, with stakeholder interviews. Fixed price: USD 5k, 10k or 15k. The result is yours.
Fixed price · from USD 5kThe plan from Discovery, delivered with your engineers on your cloud account: fixed price, time and materials, or a capped retainer. Or build it yourself.
Fixed · T&M · retainerHandover with training and documentation. Your team runs it, or we stay on for maintenance if that is the strategic choice.
Your team · or ours
Nov 15–18 · Las Vegas
Booth 127-24, Exhibit Hall. Book 30 minutes before the show: challenges and best practices for AI and data projects.
Same engineering, measured in outcomes. Three results, three projects: a registry pre-filled by clinical NLP, a billing cycle run by an agent, call analytics that found missed revenue.
60%
less documentation time in a live hospital deployment
6 FTEs
freed by a billing agent, with a 32% lower document error rate
6-fig
additional monthly revenue from calls that were already happening
“The datarabbit team was brought in to help (a) bridge a staffing gap on our DevOps team, (b) accelerate a major cloud migration project, and (c) act as an expert consultant to pressure test our planned architecture. The team performed all three exceptionally well. I plan to engage them in future projects without hesitation.”
“What stood out was their ability to quickly research and answer questions at a level that was easy to understand – and their honesty about what AI could and couldn't handle.”
“datarabbit has a team of highly capable engineers that deliver with both quality and speed. The team provides trustworthy direction.”
“The datarabbit team was brought in to help (a) bridge a staffing gap on our DevOps team, (b) accelerate a major cloud migration project, and (c) act as an expert consultant to pressure test our planned architecture. The team performed all three exceptionally well. I plan to engage them in future projects without hesitation.”
“What stood out was their ability to quickly research and answer questions at a level that was easy to understand – and their honesty about what AI could and couldn't handle.”
“datarabbit has a team of highly capable engineers that deliver with both quality and speed. The team provides trustworthy direction.”
Book an intro call: an hour with an architect about where you are, whether we are the right fit, and what a Discovery Phase would cover. Honest, even if the answer is no.
