Founding AI Engineer at Genloop - building the hard parts of making data answer for itself.

Kaushal Kumar  • Peerlist

<h3>Genloop offers the most accurate data intelligence stack for the AI world.</h3><ul><li>Connect your entire data estate in minutes to get verified answers for your team, whether human or AI.</li><li>Builds a living context graph that understands your business by connecting structured data, documents, and the apps your team uses.</li><li>Provides free dashboards with proactive, quality insights and enterprise-grade governance for team collaboration, with no seat pricing.</li><li>Enables teams to be truly AI-native by connecting to favorite AI agents, workflows, tools, or your own product through a single context layer.</li><li>Features five core capabilities: Living Context Graph, Self-Learning Loop, Deterministic Reasoning, Decision Intelligence, and Governance.<ol><li>The Living Context Graph understands your data architecture, processes, decisions, and people, refining with every interaction.</li><li>The Self-Learning Loop continuously refines its context and skills with every interaction, feedback, and job well done, unlike AI tools that start from zero on every query.</li><li>Deterministic Reasoning allows Genloop to investigate, cross-reference, and trace anomalies to their root causes, showing the reasoning behind every answer.</li><li>Decision Intelligence surfaces insights, suggests actions, tracks if actions were taken, connects outcomes with actions, and remembers what worked.</li><li>Governance ensures data teams stay in control by reviewing and verifying every update Genloop learns, maintaining accurate context and trustworthy answers with role-based access.</li></ol></li></ul>

Genloop

• Implemented a load balancing policy for a private cloud environment. • Analyzed the resource consumption of virtual machines to identify potential load balancing conflicts. • Developed a self adaptive weighted approach to resolve load balancing conflicts caused by different resource demands of cloud applications. • Incorporated a probabilistic approach to ease the problem of load crowding in the concurrent user scenario, and adjust the system accordingly achieving a significant jump in performance.