Afiniti Configuration & Rule Engine

• Category: Automation
• Company: Afiniti
• Code Repo: Company BitBucket (Private)
• Language: Python

Afiniti introduced the latest version of its call-pairing AI solution in 2020, developed using C in a Docker-based Linux environment.

Using the REST API exposed by its configuration container, I designed and developed an automation tool for streamlining the configuration process for each client. The tool, called V6lidation, was split into two parts,

Configuration

• Bulk-Upgrade Functionality - The process of deploying Afiniti on a new client requires configuring thousands of agents and agent skillsets. Through this utility, this process drastically reduced the deployment time and minimzed the risk of human error.
• Export Functionality - The ability to easily export the configuration settings from one client so they can be easily deployed on any other client.

Search Engine

• A search engine to quickly sift through thousands of agents and routing entities.

Rule Engine

Afiniti's product is a general purpose tool that can be designed to be used at a number of different telephony switches including Avaya, Genesys, and Cisco to name a few. There is a lot of configuration that needs to be changed for each switch and I, along with Fahd Khan, Program Architect at System Integration & Deployment, designed a rule evaluation engine. This engine could be provided a default schema in JSON format for each switch and it would evaluate the schema against the configured settings and raise alerts for any configuration issues.

The engine used a recursive, nested approach, allowing users to test multiple rules using basic logical operators like AND, OR, NOT and arithmeitc operations like GREATER THAN, LESS THAN, EQUAL TO, etc.

Technology Stack

• Python (Flask)
• HTML, CSS, JavaScript and Bootstrap (Frontend)