Success stories

INSURANCE COMPANY

What if... an insurance company could implement state of the art development practices and methodologies to provide an exceptional UX?

SERVICE

Team Lead, Backend and Frontend Developers

INDUSTRY

Insurance

TECHNOLOGY

Spring Boot, Java 11, Team City

The client

Vault is an insurance company that specializes in providing coverage for high-value assets and specialty risks.

Benefits

Accelerate the development and deployment of new applications and updates.
We brought a fresh perspective, new skills and ideas. Introduced innovate technologies and solutions that enhanced the organization’s services, and UX.

Challenge

  • Create the entire IT ecosystem (application, services, pipelines and dev process) from scratch
  • Materialize the product requirements into tangible results that improve clients and internal team experience with the platform.

Solutions

Digital transformation was highly required by the client due to an inefficient development process. We implemented new methodologies and best practices and rebuilt the entire process from scratch making the code easier to understand by existing and new team members.

We renewed the way the developers work on a daily basis by introducing new code standards for Java and Spring Boot framework, also migrating from Java 8 to Java 11, migrating CICD pipeline software from Jenkins to TeamCity (User Experience is totally new and more friendly).

We also revamped the entire way we deploy applications at the end of the CICD cycle by creating new bash scripts to keep track of every application artifact we release, even if its for a test environment or production. This kind of decisions were taken in order to reduce costs and error margins.

Nexts Steps

Implementing artificial intelligence to harness user statistics information effectively to enhance the platform capabilities.

What the client says

“We could not have reached this stage of the project without the efforts of the
Mindtech team, and for that we are grateful for our continued relationship and your support of our software build out.”
Graham Hillis
Director of Software – Vault

Benefits

Improving product descriptions on the online store to enhance the customer shopping experience and increase sales.

Substantial reduce the time needed to input product attributes by leveraging cutting-edge technologies.
The process of completing product attributes was cumbersome and time-consuming. It also resulted in incomplete or error filled product descriptions, impacting the user’s shopping experience.
Using computer vision, we generated product descriptions which contain information about attributes such as color, material, dimensions, size, etc. This information is published on the ecommerce along with the product images.
The project is based on the use of AI generative models, specifically Gemini Pro Vision, to achieve three main objectives:
  • Create new product descriptions by extracting attributes from product images.
  • Enrich these product descriptions using previous information from other products
  • Perform a retroactive process to update the product descriptions when new attributes are found when compared to embeddings generated by Gecko (Google model), i.e., add this information to existing similar products.
Staff Augmentation
Google Cloud Platform (GCP) was chosen for its robust cloud computing capabilities and built-in machine learning services, providing a reliable infrastructure that is highly scalable for heavy computational tasks.
Python was selected as a high-level, interpreted language with an abundance of AI-related libraries, allowing for easy readability, quick prototyping, and sophisticated AI and machine learning projects.
Docker was utilized to automate deployment and scaling of applications, ensuring the consistent operation of the AI model across various environments.
The Gemini Pro Vision Model and Text Embedding Gecko Model were used to offer specialized functionalities in computer vision and natural language processing respectively, providing capabilities such as sophisticated analysis of visual content and representing text data as normalized numerical vectors.
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