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POC Emergency Demand Prediction Algorithm for CHAI Analytics

Services Covered:

AI and Machine Learning • Big Data Analytics and Business Intelligence
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Industry
Industry

Healthcare

Duration
Duration

4 months

Budget
Budget

Less than 10K

Start Date
Start Date

1 March 2020

Team Size
Team Size

1-5

Engagement Model
Engagement Model

Nearshore

Project Capability Score (PCS)

gauge meter
74/100
Good

Project Capability Score (PCS) estimates how capable Apzumi is of successfully delivering a project like this, based on its past experience, track record, and ability to handle similar work. Learn more about PCS

Client

CHAI Analytics

map United Kingdom

Project Summary

CHAI Analytics engaged Apzumi to develop a proof-of-concept prediction algorithm to forecast emergency demand in healthcare. Apzumi provided analytics and data modeling, building a prototype algorithm in Python with a Java/Angular frontend. The prototype produced evidence that led to several partnership opportunities and the client praised Apzumi's collaborative approach and structured project management.

Key Challenges

  • Determine whether a viable prediction algorithm for emergency demand could be developed with available data.
  • Explore possible modeling approaches in a go/no-go proof-of-concept.
  • Iteratively test algorithm logic and accuracy to inform next-stage development.

Project Deliverables

  • Proof-of-concept prediction algorithm (prototype)
  • Frontend prototype built with Java and Angular
  • Data modeling and analytics deliverables
  • Test results and accuracy assessments across scenarios

Project Solution

Apzumi provided analytics and data modeling to design a proof-of-concept prediction algorithm. They developed a prototype backend prediction algorithm in Python and a frontend prototype using Java and Angular, applying iterative data science techniques to test accuracy across scenarios. The output was a prototype to validate logic and drive further platform development.

Project Outcome

  • Produced a prototype prediction algorithm that generated evidence for progressing the product.
  • Enabled acquisition of about 3–4 strong partnership candidates in the UK.
  • Improved the client's ability to convince partners to share data and continue development.

Platforms

  • WebWeb

Tech Stack

  • JavaJava
  • AngularAngular
  • PythonPython

Client Endorsement

Overall Review Rating

5star

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Thanks to Apzumi, the client was able to garner strong partnership support to move the product forward. The internal stakeholders were particularly impressed with the team's collaborative approach to the project, and their willingness to grow with the organization in the long term.”

Ram Rajaraman

Founder & CEO

Note: This endorsement is based on publicly available client feedback from external review sources.

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