Clozer

A machine learning mobile app that helps salespeople get new contacts and accelerate sales.

  • Refactored prototype

  • New functionalities

  • Integration with CRMs

What the client expected?

Challenge

CRM with machine learning

The aim was to empower CRM solutions with AI capabilities.

Integrity of data

Client data needed to be complete and consistent to streamline sales.

Close more deals

Accelerating sales with real-time data insights with minimum manual data entry.

Approach

How did we work on the project?

We were tasked with creating a hybrid mobile application that would offer standard Customer Relation Management functionalities, empowered with machine learning solutions, and innovative functionalities to guarantee the integrity of contact data.

The goal was to support natural language processing, voice chat, and interpret commands with the use of machine learning. The integrity of contact data was planned to be guaranteed with the use of a blockchain technology, which would allow synchronizing dispersed knowledge in the community of sellers.

Functionalities were fully synchronized with SalesForce, Google Calendar, and Google Contacts, with plans to introduce additional synchronizations. The application was based on a pre-existing code, which we had to refactor.

We started the project with a technological audit that pointed out what needed to be improved in the application’s architecture. We advised rewriting the front-end to React and used the architecture of loosely coupled services to improve future-proofness of the back-end.

Once the application was refactored, we started the implementation of new functionalities.

What did we achieve?

Results

The ability to transform speech to text on mobile devices was guaranteed by a custom cordova plugin, built as a wrapper for Microsoft iOS Bing SDK. We implemented machine learning functionalities with the use of Microsoft Cognitive Services - mainly LUIS. This included eg. an automatic extraction of new entities and activities from emails that were processed by the system. We implemented an intelligent SalesBot with the use of Microsoft Bot Framework.

We implemented a role management system, and with the use of GraphQL we created a single point of truth for contact data. We also added a synchronization of data with Google Contacts, Google Calendar and Salesforce.

Refactored prototype

We worked on an existing codebase that we improved

New functionalities

Added features to boost capabilities

Integration with CRMs

Including Salesforce and Google tools

Functionality

Key features

  • speech recognition on mobile devices
  • machine-learning with the use of Microsoft Cognitive Services
  • inbox emails processing with the use of machine learning - LUIS
  • intelligent voice chat interface implemented with the use of Microsoft Bot Framework
  • data synchronization with Salesforce, Google Contacts, Google Calendar
  • roles management system
  • GraphQL-based single point of truth system for identities

Get in touch

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Michał Zacher

Michał Zacher

CEO at Vazco

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