Peritus.ai is an Artificial Intelligence (AI) recommendation engine for developer self-service, but what does that mean?
It’s not as convoluted, contrived or concocted as it sounds, not at all… this is a real thing and it signifies a means for software application development engineers to self-serve (i.e. get the information they need in order to complete programming tasks) by accessing a range of community-provided (and enterprise-provided, where appropriate) information resources in a way that is more intelligently coalesced through the use of AI.
Peritus Assistant for Slack is designed to give developers informative responses to their most common questions on a range of cloud-native (typically/characteristically open source) technologies including Kubernetes, Docker, Kafka, Elastic, MongoDB and other projects.
“Developers continue to rely on community and vendor forums for expert knowledge for the most popular cloud-native topics but questions are rarely answered in under 24 hours and the best advice is posted on multiple fragmented sites,” said Robin Purohit, co-founder, and CEO, Peritus.
To bring developers instant recommendations from all trusted sources as they work, Purohit explains that Peritus has built a knowledge network of over 27 million questions, answers, tips from published content and conversations on Stack Overflow, related community product forums and GitHub for a total of 25 of the leading open source and proprietary cloud-native technologies.
Problem spanking question ranking
The Peritus Recommendation Engine uses machine learning and AI to source and rank all of the information by filtering the answers provided by over one million qualified community experts to help developers quickly find the best responses to their questions.
Previously available as a Chrome Extension for community forums, developers can now also tap into this comprehensive knowledge network through the Peritus Assistant for Slack.
Slack has rapidly become an essential channel for community engagement, particularly for developer-first communities. According to IDC, developers spend 21% less time identifying and resolving engineering-related bugs and issues when using Slack. The Peritus Assistant for Slack extends this power even further.
The Peritus Assistant uses instant machine learning to provide recommendations on Slack developer communities by understanding the context of a long-form technical question and identifying the best answers.
It provides the responses using @askPeritus via direct message or through a reply to the developer to review and post to the channel. Based on the question, the Peritus Assistant for Slack also recommends the top three experts to contact for additional help across multiple communities based on the specific topic of the query.