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InsurTech

Launching an InsurTech Platform

with SAANS Health

Keywords

Insurance Products, AI, ML, HIPAA

Services Rendered

Product Design

Product Engineering

Continuing Design

Tech stack

GitHub Secrets, Selenium, RabbitMQ, Okta, ReactJS, Spring Boot

Introduction

In partnership with SAANS Health, we managed ambiguities and engineering complexities with continuous design, user testing, technology spikes, and agile execution to streamline the launch of this InsurTech marketplace.

iNDUSTRY CHALLENGE

SAANS Health has a proprietary AI/ML platform, AiQ, where augmented intelligence is an accelerator to bring healthcare products to the market. An InsurTech company was using Care and Risk AiQ to build a new insurance marketplace. This insurance marketplace would empower small and medium businesses to negotiate cost-optimized insurance plans.

Zemoso Labs Partnership Challenge

Zemoso’s expertise played the pivotal important role in Insurance, AI-ML, and zero-to-one expertise together to identify what really mattered to the end-user, and launch the MVP in 6 months.

  1. Integrate SAANS Health AiQ within the InsurTech platform so that it could be leveraged seamlessly
  2. Solve the every-evolving complexities of carrier integrations to extract/retrieve claims data through SMBs
  3. Set up protocols to reinforce user authentication around sensitive data, and continuous HIPAA compliance

Impact created

We co-created a high-fidelity prototype in four weeks and created an incredibly detailed design system to ensure execution consistency in 6 weeks by timeboxing everything.

4 weeks

Hi-Fi prototype

6 weeks

Design system

What are our clients saying?

Our clients love what we do:

Zemoso has been an incredible collaborative partner in helping translate our ideas into market-ready products. The leveraging of continuous design throughout the development lifecycle is invaluable in incorporating user centricity into every phase of the life cycle.

Raju Kattumenu, CEO and Founder

SAANS Health

How did we do this?

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We ran an architecture sprint to create a logical and technical architecture. Some heuristic decisions were made over tech-stack choices. The platform leverages the modular benefits of a microservices architecture. The front-end was built using React JS, and using atomic design principles. Backend was built using Spring Boot. QA automation, CI/CD, etc. were of course built into the delivery lifecycle.  

The core of the platform: Data

Key challenge: Member-mediated data access

Access to Health Data for SMBs is critical to their ability to negotiate and procure cost-advantaged health insurance. At the core of the platform is a data retrieval system used to fetch member data from insurance carrier portals. This entire process is member-mediated. Selenium-based robotic process automation and secure API interfaces were used to interface and retrieve data on behalf of the member. AiQ analyzes this extracted data and provides reports to SMBs to help them negotiate a better deal for their employees. Insurance vendors use these insights to provide informed proposals. We also used RabbitMQ messaging layer to queue the data extraction process, and in doing so, the platform could balance the load optimally. ‍

The crux of the solution - a marketplace of disaggregated insurance products

Key technical challenge : field matching and alignment

The workflow for the SMB marketplace required vendors to submit their proposals into the system. Due to the variability in the inputs from the various vendors, we incorporated a fuzzy search mechanism to create consistency in the representation of the various quotes to the end user, so that they can easily compare and select.

Security measures - encrypted at rest, and access-controlled

Access to the sensitive health data of an individual from within an insurance carrier’s database is member-controlled. Okta gates access to this health data (from any other insurance provider or employer) within the InsurTech platform with strict user authentication protocols.    

The secrets management process stores the member credentials in the database in an encrypted state. This is decrypted only when the Selenium bot needs to run the API call into the insurance provider’s database. All member information for access to API-based data sources is stored in GitHub Secrets, ensuring end-to-end security.

Mapping system for the database

A mapping system was built to give developers more control over the data retrieval and transformation process. This allowed for consistency of processing through the AiQ platform.

Conclusion

In the end, it was an irrefutable, all-encompassing win as we helped the InsurTech client onboard their first customers and pressure test what we’ve built together.

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