Expert AI ARCHITECTURE AND PRODUCT CONSULTANTS

Developed an AI-powered Knowledge Management System delivered as a SaaS platform, designed to unlock enterprise knowledge at scale and accelerate decision-making. Built with a cloud-native, multi-tenant SaaS architecture, the platform seamlessly integrates with leading enterprise systems such as Jira, Confluence, SharePoint, LeanIX, and other knowledge sources, creating a unified and intelligent knowledge layer across the organization.

Deployed on the Microsoft Azure platform, the solution leverages Azure Functions for scalable, event-driven processing and Azure OpenAI to enable advanced semantic search, contextual retrieval, and natural language interactions. By transforming fragmented documents and data into actionable insights, the platform empowers teams to find the right information faster, improve productivity, and drive consistent, informed outcomes across the enterprise.

AI-powered, multi-agent RFQ extraction solution purpose-built for energy companies to accelerate and standardize the quotation lifecycle. The platform intelligently ingests RFQs from images, scanned PDFs, native PDFs, and Excel files, automatically extracting, validating, and structuring commercial and technical requirements with high accuracy.

Leveraging a multi-agent AI architecture, specialized agents collaborate to interpret specifications, identify line items, normalize units, and flag inconsistencies, significantly reducing manual effort and turnaround time. Seamlessly integrated with the enterprise sales portal, the solution enables sales teams to convert RFQs into structured opportunities, quotations, and proposals faster and with greater confidence.

AI-powered operational workflow automation platform designed to transform IT and business operations from reactive to self-healing. The solution intelligently orchestrates end-to-end workflows with auto-healing capabilities, automatically detecting issues, triggering remediation actions, and minimizing service disruption.

Leveraging historical knowledge and past incident data, the platform automatically enriches tickets with contextual work notes, enabling faster diagnosis and resolution while reducing dependency on manual intervention. Machine learning–driven auto-approval models streamline routine operational decisions, accelerating turnaround times without compromising governance or compliance.

A built-in multi-environment log analyzer continuously monitors logs across development, test, and production environments, proactively identifying critical errors and early warning signals. The platform provides intelligent recommendations and actionable insights, helping operations teams prevent incidents, improve system reliability, and achieve measurable reductions in mean time to resolution (MTTR).

Successfully delivered Warehouse Management System (WMS) initiatives focused on data analytics, operational efficiency, and intelligent optimization. These projects included the design and implementation of a scalable Data Warehouse on Google Cloud Platform (GCP) to centralize warehouse, inventory, and transactional data, enabling real-time insights and informed decision-making. Advanced shortest path algorithms were implemented to optimize warehouse navigation and picking routes, significantly improving fulfillment efficiency. In addition, item grouping and classification models were developed to support intelligent coupon and promotion management, enabling targeted offers and improved inventory movement. 

Network transformation with transitioning from public IP–based access to private IP architectures, significantly reducing exposure to external threats and attack surfaces. By adopting private networking, secure endpoints, and controlled access patterns, the solution ensures that critical applications and data remain isolated within trusted network boundaries.

This transformation is complemented by a comprehensive data governance framework, establishing clear controls over data access, classification, and usage across the enterprise. With built-in policies for compliance, auditing, and lifecycle management, organizations gain improved visibility, regulatory alignment, and confidence in how sensitive data is protected and consumed.

Built and scaled a robust SaaS Applicant Tracking System (ATS) tailored for the US mid-market, enabling fast-growing businesses to modernize and streamline their hiring operations. Designed with a SOA and microservices architecture, the platform delivers high scalability, resilience, and rapid feature rollout to meet evolving customer demands. Performance and reliability are ensured through read/write database segregation using master–slave configurations, supporting high user concurrency and peak hiring cycles. Seamless social login capabilities accelerate user onboarding, while enterprise-grade Role-Based Access Control (RBAC) ensures secure, compliant, and multi-tenant operations. Together, these capabilities position the ATS as a secure, scalable, and market-ready solution for mid-sized enterprises.