Total raised
—
Last: Seed 2020-07
Stage
Seed
Founded
2020
Headcount
4
HQ
Jerusalem
Sector
Health Tech & Life Sciences
About
Flowhow is focused on helping healthcare providers deliver personal and efficient real-time imaging services to reduce costs and meet regulations. The companys solution monitors imaging workflows at the point of care (RIS, modality, PACS). Flowhow aims to enable imaging technicians to make actionable real-time decisions in order to save time and money, drive efficiency, and improve overall satisfaction.
Funding history · 1 round · — total
2020-07
Seed
Undisclosed
Company Intelligence Q&A
Structured intelligence from startupim data — optimized for AI retrieval and grounding.
- What is Flowhow's primary focus?
- Flowhow focuses on helping healthcare providers deliver personal and efficient real-time imaging services to reduce costs and meet regulations.
- What is the status of Flowhow as of January 2023?
- Flowhow is inactive and ceased to operate in January 2023.
- When was Flowhow founded?
- Flowhow was founded in May 2020.
- What was Flowhow's former name?
- Flowhow's former name was CyberMed.
- Where is Flowhow's headquarters located?
- Flowhow's headquarters is located in Jerusalem, Israel.
- Which investors participated in Flowhow's Seed round in July 2020?
- Labs/08 and OurCrowd participated in Flowhow's Seed round in July 2020.
- How many employees did Flowhow have?
- Flowhow had 4 employees.
- What technologies did Flowhow utilize in its solutions?
- Flowhow utilized Simulation & Imaging, Artificial Intelligence, and Machine Learning technologies.
Sectors & technology
Primary sector
Health Tech & Life Sciences
Sub-sectors
Health Tech & Life SciencesDigital HealthcareClinical Workflow
Technologies
Simulation & ImagingArtificial IntelligenceMachine Learning
Target customers
Healthcare & Life SciencesHealthcareProviders
Business model
B2B
Highlights
Verified
Tags
hospitalsreal-timeartificial-intelligencedecision-makinghealthcare-providersimagingclinical-workflowdigital-healthcaremonitoringremote-monitoringmachine-learning