VoiceBase

An AI-based platform for real-time analysis of conversational interactions. Get insights from the customers, improve the performance of call center agents, and increase sales.

Industry AI

Duration: Ongoing

Team: 5

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Technologies utilized

Docker. kubernetes, prometheus, twillo, kotlin,
maven, sonerqube, kafka, nats,
pulsar, grpc, socket io, ring central guava,
junit 5, grafana, redis, spring, Java

Team composition

1 Java Tech/Team Lead,
2 Java Developers,
1 NodeJS Developer,
1 DevOps

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CLIENT

VoiceBase, Inc.

An innovative US IT company that develops AI and ML-based voice analytics solutions for business.

Challenge

The client’s platform consists of a number of microservices enabling the platform’s functionality. They interact through different communication protocols that may result in a high risk of bugs and difficulties in its maintenance.

The client required to introduce the single (custom) protocol to improve platform's stability and reduce costs for support.

Additionally, the customer needed to extend its market share by adopting it for communications through cloud platforms, such as Twilio and RingCentral.

Features

Architecture

Design and creation of a stream-based communication framework between services that can be built on many streaming providers (Kafka, Pulsar, Nats). It includes a topology of relationships and an algorithm for performing actions based on received events within the system.

Metrics

We introduced metrics for the platform. Individual real-time microservice and configured alert notifications allowed to simplify adding new metrics and their management, as well as faster tuning of the system parameters with large volume of data.

Testing

Created standard integration test tool allows us to faster test each service, detect bugs, verify the whole real-time flow, and increase the level of the system stability. The tests results reports were generated within CI/CD flow.

Business values

In-depth Analysis

A comprehensive analysis has clarified business requirements and developed technical requirements. It allowed to build a clear architecture for the communication framework and custom protocols.

Smooth Functionality

Deployed integrations with the cloud communication platforms, introduced metrics, and developed automation test tool, performed testing and bug fixing has ensured flawless work of the software.