endorsedOngoing

Cash Flow Projection Application for Insurance Software Firm

Services Covered:

Custom Software Development

Industry

Information Technology

Duration

123 months

Budget

10K - 49K

Start Date

1 May 2016

Team Size

1-5 Employees

Engagement Model

Offshore

Project Capability Score (PCS)

81/100

Strong

Project Capability Score (PCS) estimates how capable DICEUS 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

Confidential

Springfield, United States of America

Project Summary

Diceus developed an internal cash flow projection (budgeting) application for a property-casualty insurance software company, building the app in Python and deploying it on AWS. They adopted the client’s technology stack (Python, Flask, AWS) and implemented monitoring and logging via CloudWatch and CloudTrail while learning Pandas-based data transformations. The client praised their rapid ramp-up, flexibility across time zones, and cost savings versus internal estimates.

Key Challenges

Needed overflow development capacity while the internal team focused on the primary product (BriteCore)
Build an administrative cash flow-forecasting/budgeting application
Require work in the client’s specific technology stack (Python, Flask, AWS) despite the vendor's prior .NET experience
Avoid using a standard SQL database and instead use Pandas DataFrames for ETL and data transformations
Concern about coordinating across significant time zone differences

Project Deliverables

Cash flow projection application
AWS-deployed Flask application
Monitoring and logging via AWS CloudWatch and AWS CloudTrail
Initial screen designs

Project Solution

Diceus built a cash flow projection/budgeting application using the client’s technology stack. They learned and applied Python and Flask, deployed the application to AWS, and configured monitoring and logging using AWS CloudWatch and AWS CloudTrail. The team adopted the client’s data approach, using Pandas DataFrames for ETL and transformations, and iterated on initial screen concepts with a graphic designer before continuing development with a single programmer.

Project Outcome

Significant cost savings versus the client's internal estimate (projected ~ $60,000–$100,000 comparison referenced)
Rapid ramp-up in the client's Python toolset (reach useful proficiency in about a month)
Maintained availability and collaboration despite time zone differences
Delivered satisfactory quality code in line with the client's timeframe expectations

Platforms

Tech Stack

Python
Flask
Amazon Web Services (AWS)
AWS CloudWatch
AWS CloudTrail

Client Endorsement

Overall Review Rating

4.75

Timeliness

Cost Rating

Willing to Refer

Quality of Deliverables

“Diceus picked up unfamiliar technologies and used them effectively to deliver satisfactory quality code in line with client's timeframe expectations.”
Phil Reynolds
CEO
Date: 11/17/2016