WibiData

San Francisco, CA, United States

Healthcare Infrastructure AI / ML PreventionShut Down

Developed enterprise data applications for personalized customer experiences, specializing in real-time predictive analytics, machine learning, and recommendation engines, but ceased operations in 2015.

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Check out WibiData on @MedStartr Today Developed enterprise data applications for personalized customer experiences, specializing in real-time predictive analytics, machine learning, and recommendation engines, but ceased operations in 2015. #MentalBehavioralHealth #HealthcareInfrastructure #AIML #Prevention #MedMo #MedStartrVentures

https://www.medstartr.ai/s/l-O-G8Hqf6g

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Problem Statement

WibiData developed enterprise data applications for personalized customer experiences.

Core Technology

Apache Hadoop, Apache Cassandra, Apache HBase, Apache Avro, Kiji Project, entity-centric storage architecture, real-time predictive analytics and Next Best Action modeling, machine learning and data science applications

Key Differentiators

Entity-Centric Storage architecture; Real-Time predictive analytics and Next Best Action modeling; Machine Learning and Data Science applications; Recommendation engines for personalized content delivery; Omni-channel brand experience across web, mobile, and in-store; Unify data from multiple sources (CRM systems, email marketing, web logs) to build comprehensive customer profiles and deliver dynamic, data-driven interactions at scale

Company Info

Business Model: B2B
Founded: 2018
Total Funding: Only accessible to MedStartr community members. Join now
Only accessible to MedStartr community members.
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Website: www.crunchbase.com/

Disease Areas

Mental Health

Technologies

Recommendation EnginesEnterprise Data ApplicationsApache HadoopApache CassandraApache HBaseApache AvroKiji ProjectMachine LearningData SciencePredictive AnalyticsBig Data

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MedStartr Engagement Score

The MedStartr Index is a reflection of how the crowds that come to MedStartr everyday to find healthcare innovations reacted. Calculated by our AI agent Fyggy based on algorithms we have been building since 2012 and over 100 different factors, the math is proprietary and complex. Suffice to say, it has been found to be highly correlative with early stage company growth. What you see here is the public version. To learn more or to get deeper access to our predictive data on startup success for your fund or company, click here.

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What do you think of WibiData?

A HUGE part of what early stage companies, and even late stage ones, need and get on MedStartr is honest feedback from actual patients, clinicians, hospital leaders and industry insiders. It is very easy to get tunnel vision as a founder. Please tell the team that runs this company what you think.

Clinical Benefit Potential

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Feasibility

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Innovativeness

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Fundability

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Scalability

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