We connect many hospital sites, each with its own identity system, and adding or removing users across them is slow and error-prone. We need a solution that federates with a wide range of hospital identity providers, automates provisioning and offboarding, keeps clear audit trails for regulated work, and prices simply per connected site. Proven references in clinical settings matter.
Healthtech · Clinical Software · 1000+ · North America #b027_10
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We provide cloud practice software for independent medical practices, covering records, billing and patient marketing, formed by combining earlier product lines.
- Industry
- Healthtech · Clinical Software
- Size
- 1000+ employees
- Region
- North America
- Tools budget
- $20K+ per month
- Needs
- Data pipelines & integration. We need dependable pipelines turning practice and billing records into training data for our new AI features.Data quality & observability. Bad records slip into analytics and model training unnoticed, and we usually learn about it from downstream users.Cloud security posture. We run a mix of older data centers and newer cloud workloads, and keeping both secure against several frameworks is hard.
- Expects from suppliers
- Works with our existing lakehouse and orchestration tools; Lineage and quality alerts for health data; Posture checks spanning hybrid environments
- Not a fit
- Point products that only cover one cloud; Vendors without payment card compliance experience
- Stack
- cloud: GCP-class hyperscaler, data warehouse: cloud, on-prem / private cloud, EHR system in place
- Buying triggers
- AI adoption push, tool consolidation
Needs
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We hold customer traces packed with sensitive context, and our detection and response coverage is still thin. We need cloud-native monitoring tuned for SaaS and Kubernetes logs, alerts that surface real threats instead of noise, and a rollout that keeps pace with our fast hiring. Cloud-delivered only, and affordable for a mid-sized team.
We extract many variables from clinical notes, and each one needs a clinician to check it before we share data with research partners. By hand, that review is slow and eats our small team's time. A good solution must flag likely errors, sample smartly, track reviewer decisions, run inside hospital walls, and stay affordable for us.