Flame is an AI platform for enterprises. This is an ambitious project undertaken by Atalgo Engineering team where we are aspiring to model all the processes of an enterprise on a single platform and build a comprehensive knowledge base of the organization which can be exploited by Generative AI to automate and smarten various tasks.

At high level, we see an enterprise comprised of two types of processes – Business and Technical. Examples of business process are Account Creation, Reconciliation, Fulfillment etc. where examples of technical process are Code Development, Testing, Deployment, System Maintenance etc. As businesses of all types are increasingly becoming more technology driven, technical processes are becoming equally important. They play a pivotal role in supporting an organization’s business processes. Introducing efficiencies in business processes can provide significant cost savings and competitive advantage.

Flame is a generative AI based platform with an architecture specifically designed to support enterprises.. We model three aspects of an organization’s processes as ongoing basis –

1. Toolsets being used
2. Learnings gained so far
3. Ongoing learning by virtue of using Flame

At a high level, the entire organization will be modelled at three layers –

Project -> Process -> Flame Component

Project is defined as a common objective of the organization which can be achieved by multiple processes. Project also signify a group of personnel within organization supporting a common goal. Multiple processes can be associated with a project

As discussed above, a process can be either technical or business and using different set of toolsets such as Salesforce, SAP, Jenkins, Jira etc. We develop a Flame model of all toolsets necessary to complete the process as Flame Components.

Flame Component (FC) is a foundational and most critical aspect of Flame design and functionality. FC will model the solution space of any task that will be undertaken by Flame engineers on the Flame platform.

Flame Components will be used to model below knowledge artefacts –

1. Toolsets – internal and external
2. Data while resides in various databases which in turn is leveraged by the toolsets.
3. Ongoing activity of the organization personnel executing those processes

Flame aspires to model all the above in such a way that it eventually starts acting as an intelligent knowledge repository for their employees. Also, Flame AI stack would aim to generate new knowledge aimed at solving new challenges. This is where Flame Components will play a major role in the design of Flame as an intelligent hyper automation engine.