Engineering practical AI systems, agentic workflows and enterprise solutions.
Chennai, TN7+ Years of Experience
ENGINEER · BUILD · DELIVER
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Selected work
Projects & case studies
Engineering work across enterprise AI delivery and the AegisMike platform—showing what I have implemented, what I am building and the technical direction behind each initiative.
Personal project · In progressEnterprise AI adoptionAI engineering operationsCustomer-specific delivery
AegisMike – Enterprise AI Engineering & Management Platform
AegisMike is my independent AI engineering platform initiative and long-term ambition: to make AI adoption easier for organisations across the world. I am shaping it as an engineering environment for discovering business problems, designing and assembling AI solutions, testing them with controlled data and simulations, and delivering tailored applications into customer-managed environments. The goal is to turn fragmented, one-off AI projects into repeatable, governed and provider-independent engineering workflows that can be adapted to different industries and operating environments.
Long-term mission
Make practical AI adoption accessible to organisations worldwide.
AegisMike is being developed toward a reusable engineering platform for taking AI from idea to validated, customer-ready solution—across industries, models and deployment environments.
Deployment options
Designed to fit the organisation’s infrastructure and operating requirements.
Fully On-PremisesCloudHybrid
Platform components
Customer Solution FactoryProject WorkspacesProject-based Data SourcesSimulation Studio & Dataset CatalogModel & Provider ManagementAgents, Tools & OrchestrationAI Development StudioAnalytics StudioGovernance, Audit & Cost Visibility
AegisMike subprojects
AegisOps · AI Incident Intelligence CopilotMVP
AegisMike subproject. A built engineering project for IT incident investigation, combining RAG, structured tool calling and ML-based escalation-risk prediction. Includes customer-profile, open-ticket, escalation-risk, vulnerability and knowledge-base tools; Sentence Transformers with Qdrant; and a Scikit-learn logistic-regression risk model.
AegisFlight · Aerospace Data EngineeringIn Progress
AegisMike subproject. An aerospace-focused initiative to generate realistic synthetic flight-recorder datasets for flight-data analysis, anomaly investigation and model development. The planned scope includes phase-based flight time series, labelled anomaly scenarios, data-quality cases and reproducible dataset exports.
Architecture direction: The internal AegisMike engineering environment is planned for GCP, including a simulation data library. Customer solutions are intended to be deployed independently in customer-managed environments. These capabilities describe the product vision and roadmap; they are not represented as completed or generally available functionality.
Designed and implemented within my ManageEngine Analytics Plus role to bring product knowledge, senior-technician troubleshooting practices and AI-assisted communication directly into customer and technician support workflows. The suite contains two distinct solutions: a customer-facing product-support chatbot for Analytics Plus, and a technician-facing AI copilot embedded in Zoho Desk.
Customer-facing chatbotWebsite and in-product support · approximately 80% chat coverage · approximately 90% success rate
Reported impact: Handles approximately 80% of incoming support chats, with an approximately 90% success rate.
Available where customers need it: Accessible from the public ManageEngine Analytics Plus website and embedded within the Analytics Plus application.
Knowledge-grounded product assistance: Answers Analytics Plus product questions using product documentation, knowledge-base articles, release notes and troubleshooting guides.
Self-service support: Helps customers resolve common product questions through conversational assistance, reducing the need to wait for a support technician.
2. Technician-facing AI copilot — inside Zoho Desk
Technician-facing AI Copilot demonstration — ticket investigation, response assistance and support workflow.
Reported impact: Approximately 50% reduction in technician workload by reducing repeated manual research, accelerating response preparation and making experienced troubleshooting knowledge easier to access.
AI First Response: Drafts an initial customer response based on the ticket context and relevant product knowledge.
Senior-technician-style investigation guidance: Generates separate internal notes recommending what to check next, likely investigation paths and practical troubleshooting steps. This helps newer technicians follow structured investigation approaches and learn from established support practices.
Historical Ticket Retrieval: Uses a dedicated retrieval capability to find similar past tickets and surface their investigation steps and resolution context, helping technicians reuse relevant case knowledge instead of starting from scratch.
AI Thread Replier: Drafts contextual follow-up replies for subsequent messages in an existing ticket conversation, keeping the response aligned with the ticket history.
Unified Solution & Email Assistant: Provides a single ChatGPT-like interface inside Zoho Desk where technicians can ask product and troubleshooting questions, discover relevant solutions and draft customer-facing technical emails.
Knowledge and retrieval foundation: Product documentation, knowledge-base articles, release notes and troubleshooting guides ground product-support responses. Historical-ticket retrieval separately brings similar past cases into the technician First Response workflow.
Implementation: Analytics Plus website and in-application chatbot experiences, Zoho Desk integration, Deluge automation, dedicated technician workflows, retrieval tools and LLM-powered assistance.
What I work with
Engineering capabilities
Engineering focus: designing, building, integrating and evaluating AI systems that solve practical problems and lower the barriers to enterprise AI adoption.
An aeronautical engineering background combined with continuous learning in software, data and AI technologies.
ED
B.Tech · Aeronautical Engineering
Hindustan University · Chennai, India · June 2016 · CGPA 8.98
01
SQL (Advanced)
HackerRank
02
Foundations of Data Science
Google / Coursera
03
Python Programming
Google / Coursera
Professional background
Experience across enterprise technology
Business use-case discovery, enterprise account ownership, analytics delivery, AI engineering, automation and stakeholder management.
Aug 2022 – Present · Zoho Corporation · Chennai
Senior Technical Consultant (ETAM) | ManageEngine Analytics Plus
While my role spans enterprise technical consulting and analytics, my primary focus over the past three years has been designing and delivering workflow automations and deploying AI-powered solutions for real business and support use cases.
Automation & AI solution deployment: Lead the design and implementation of workflow automations, AI assistants and agentic solutions, taking use cases from discovery through integration, deployment and adoption.
Business use-case discovery: Work with enterprise customers and internal stakeholders to understand operational challenges, map business processes and translate requirements into practical automation and AI solutions.
Enterprise account & engagement management: Own technical engagements, manage key customer relationships, coordinate escalations and align solution outcomes with customer expectations.
Analytics & dashboard engineering: Delivered 500+ interactive dashboards, defined business and ITSM KPIs, and developed SQL-based reporting for operational visibility and decision-making.
AI engineering: Build RAG-powered assistants, AI copilots and agentic workflows that connect enterprise knowledge, retrieval capabilities and business tools to support processes.
Integration & stakeholder delivery: Integrate systems using APIs, Zoho Deluge, MCP and related technologies; lead technical discussions, coordinate cross-functional teams and drive delivery through to resolution.
Apr 2021 – Jul 2022 · Tech Mahindra · Chennai
Associate Technical Support
Provided Level 2 support for application, infrastructure and integration incidents within SLA commitments. Used SQL analysis and structured troubleshooting to diagnose incidents and coordinate escalations.
Jan 2018 – Mar 2019 · Cyient Limited · Bengaluru
Assistant Design Engineer
Developed Aircraft Maintenance Manuals (AMM) and Illustrated Parts Catalogues (IPC), with focus on technical accuracy and regulatory compliance.
Mar 2017 – Jan 2018 · Hindustan Aeronautics Limited (HAL) · Bengaluru
Graduate Apprenticeship Trainee
Supported maintenance and overhaul of aircraft gas turbine engines, applying structured troubleshooting, root-cause analysis and engineering practices.
The bigger picture
Engineering AI for the real world
My goal is to turn complex business and operational challenges into dependable AI-powered products. I want to work at the intersection of software engineering, data, machine learning and applied AI—taking solutions from problem discovery and system design through implementation, deployment and continuous improvement.
01
Solve meaningful problems
Understand the people, workflows and constraints first. Define what success looks like, then use technology where it creates measurable value.
02
Engineer beyond the prototype
Bring together sound system design, reliable data pipelines, machine learning and agentic AI to build solutions that can operate in real environments.
03
Make AI useful and trustworthy
Prioritize grounded outputs, security, human oversight, observability and clear evaluation—so teams can understand, control and improve what they deploy.
04
Build alongside the people who use it
Work closely with users and stakeholders, iterate quickly, learn from production feedback and take ownership from the first conversation to the delivered outcome.
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Contact Me
Interested in AI engineering, enterprise automation or practical technology solutions? Feel free to connect.