FLAME USE CASES
We propose that Flame can be utilized to efficiently solve complex enterprise problems by employing its computational intelligence framework, we have been focusing on few challenging enterprise use cases and getting great results. These enterprise use cases for our Generative AI based platform are common place in enterprise IT development and maintenance environments an require significant investment. Any efficiencies gained in this space will result in significant return on investment and help organization develop competitive advantage. The current enterprise use cases Flame is being employed at are
INTELLIGENT
KNOWLEDGE BASE
Repository of dynamic knowledge artefacts which consist of multiple sources of information such as Confluence, SharePoint, Jira, CRM etc which can be queries and reasoned upon by Flame client interface. End users can ask queries requiring reasoning and context awareness and get useful and immediate response summarized by Flame engine after analyzing multiple data sources. Our architecture ensures accuracy by making sure that reasoning is done on the knowledge artefacts of the organization only. This can act as an intelligent assistant used by the entire organization.
INTELLIGENT
QUALITY ENGINEERING (iKE)
Atalgo provides a comprehensive Quality Engineering framework to manage the quality aspects of an enterprise software development project. This involves learning about the application, environment and quality metrics while driving mainstream quality tools such as Selenium, JMeter, SonarQube etc to ensure full scale quality assurance using computational intelligence.
SYNTHETIC DATA
GENERATION
Synthetic Data Generation is niche use case Flame has mastered to assist with the test data engineering and ML training. Production like fake data helps quality engineers test the solution better and can be used for other use cases such as performance testing and ML model training. Flame synthetic data generator is capable of understanding the data model, structure and the logic of data and can generate fake data at scale as a background process. This will help organizations use single platform for multiple use cases and bring the DataOps maturity to their development process
MLOps
Atalgo provides a comprehensive Quality Engineering framework to manage the quality aspects of an enterprise software development project. This involves learning about the application, environment and quality metrics while driving mainstream quality tools such as Selenium, JMeter, SonarQube etc to ensure full scale quality assurance using computational intelligence.Atalgo provides a comprehensive Quality Engineering framework to manage the quality aspects of an enterprise software development project. This involves learning about the application, environment and quality metrics while driving mainstream quality tools such as Selenium, JMeter, SonarQube etc to ensure full scale quality assurance using computational intelligence.
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