US 12,112,297 B1
Method and system for integrated analysis of data from multiple source environments
Dheeraj Pandey, San Jose, CA (US); Manoj Agarwal, Palo Alto, CA (US); Brent Chun, Rancho Palos Verdes, CA (US); Bhavana Thudi, Fremont, CA (US); Ken Chen, San Francisco, CA (US); Nimar Arora, Union City, CA (US); Brian Byrne, Issaquah, WA (US); Steven Poitras, Los Gatos, CA (US); Anindya Misra, Arlington, VA (US); and Jan Olderdissen, Herrenberg (DE)
Assigned to DevRev, Inc, Palo Alto, CA (US)
Filed by DevRev, Inc., Palo Alto, CA (US)
Filed on Feb. 11, 2022, as Appl. No. 17/670,359.
Claims priority of provisional application 63/148,987, filed on Feb. 12, 2021.
Int. Cl. G06Q 10/101 (2023.01); G06Q 10/0631 (2023.01); G06Q 10/0639 (2023.01)
CPC G06Q 10/101 (2013.01) [G06Q 10/0631 (2013.01); G06Q 10/0639 (2013.01)] 18 Claims
OG exemplary drawing
 
1. A method, comprising:
receiving first data from a development ecosystem, wherein the development ecosystem corresponds to a first system used to develop a technology product;
receiving second data from a non-development ecosystem, wherein the non-development ecosystem corresponds to a second system corresponding to end-use of the technology product;
generating a combined set of data from both the first data from the development ecosystem and the second data from the non-development ecosystem;
performing machine-learning (ML) on the combined set of data from both the development ecosystem and the non-development ecosystem; and
funneling results from performing ML-based analysis into multiple levels of funneled data objects;
wherein the machine-learning performed on the combined set of the data from both the development ecosystem and the non-development ecosystem comprises automatic processing of the data to generate a database stored in a tangible machine-readable medium comprising both raw data and categorized data, where correlation is performed against the raw data and the categorized data from both the development ecosystem and the non-development ecosystem.