Years in building ventures and shipping real-world products now bringing that execution mindset to a long-term role in a high-performing team.
Expertise
Gen AI & Product
Experience
12+ Years
Years Experience
Efficiency Gain
Users Scaled
Growth Impact
A proven track record of building, scaling, and optimizing technology products.
Self-started IT operations, gaining hands-on experience in full-stack development and client requirements gathering from home.
Led digital transformation projects. Designed AI agents and SaaS platforms that delivered 40% cost reductions for finance & retail clients including few industries.
Managed end-to-end product lifecycle for an ed-tech verification platform. Raised $110k seed funding and reduced process time by 98%.
Vice President & Support Ambassador. Demonstrated leadership by driving 20% membership growth through strategic engagement.
Currently scaling e-commerce brands while seeking a stable, high-impact role in a forward-thinking organization.
Demonstrating capability to deliver complex technical solutions.
Designed an AI-driven system to qualify and route leads in real time, transforming CRM from a database into a revenue engine.
Built a custom CRM with predictive dashboards to give leadership real-time and forward-looking visibility into pipelines.
Developed AI agents to automate repetitive internal workflows with human-in-the-loop safeguards.
UpGrad & Microsoft
Meta
Dhruv Rathee (NAS Academy)
Ankur Warikoo
Vanessa Van Edwards
Amazon Web Services
Amazon Web Services
Dr Jeff Conwall
Frequent Speaker on AI Adoption & Digital Transformation
Judge at IBM SkillsBuild Innovation Pitch
20% Membership Growth at BNI Network
Led Multiple Founder & Business Growth Sessions within professional communities
Built and Scaled Funded & Bootstrapped Ventures
Delivered Cross-Industry AI & Product Solutions
I am actively interviewing for full-time roles. If my profile aligns with your needs, please reach out.
Sales teams often waste a significant amount of time on unqualified or low-intent leads. Manual lead screening, delayed follow-ups, and inconsistent qualification criteria result in:
• Slow response times
• High customer acquisition cost (CAC)
• Lost opportunities due to delayed engagement
In many growing businesses, CRM systems existed, but were used passively, not as intelligent sales enablers.
I designed and implemented an AI-driven lead qualification and sales automation system that actively supported sales teams instead of burdening them.
• Automatically analyzed incoming leads from multiple channels (website, ads, forms)
• Classified leads based on intent, budget signals, behavior, and relevance
• Routed high-quality leads instantly to sales teams
• Triggered automated follow-ups for warm and low-intent leads
This transformed the CRM from a data repository into a decision-making engine.
Financial service teams struggled with:
• Fragmented client data
• Delayed reporting
• Limited visibility into pipeline health and future revenue
Decision-making relied heavily on manual reports and intuition, leading to missed risks and reactive management.
I led the design and delivery of a custom CRM platform enhanced with predictive dashboards, tailored specifically for financial clients.
The system unified customer data, transactions, and engagement history into a single interface, while dashboards provided real-time and forward-looking insights.
Key features included:
• Centralized customer and transaction management
• Predictive indicators for deal closure probability
• Visual dashboards for leadership and operations teams
Internal teams often spend excessive time on repetitive, low-value operational tasks such as:
• Data entry and validation
• Status reporting
• Routine internal coordination
These tasks increased costs, introduced human errors, and distracted teams from strategic work.
I designed and deployed AI agents for internal operations, focused on automating repetitive workflows while maintaining human oversight.
The agents handled:
• Data collection and validation across systems
• Automated report generation
• Trigger-based internal notifications
• Routine operational checks with escalation rules
The approach followed a human-in-the-loop model, ensuring reliability and control.