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Schedule Interview NowMy name is Sarvagya M. and I have over 2 years of experience in the tech industry. I specialize in the following technologies: OpenCV, Python, Machine Learning, PyTorch, Natural Language Processing, etc.. I hold a degree in Bachelor of Technology (BTech). Some of the notable projects Iβve worked on include: π« Automated Airport Turnaround Monitoring via CCTV + Gantt Charts, π Document Classification with LayoutLM, π OCR Automation for Insurance Forms. I am based in Bengaluru, India. I've successfully completed 3 projects while developing at Softaims.
Information integrity and application security are my highest priorities in development. I implement robust validation, encryption, and authorization mechanisms to protect sensitive data and ensure compliance. I am experienced in identifying and mitigating common security vulnerabilities in both new and existing applications.
My work methodology involves rigorous testingβat the unit, integration, and security levelsβto guarantee the stability and trustworthiness of the solutions I build. At Softaims, this dedication to security forms the basis for client trust and platform reliability.
I consistently monitor and improve system performance, utilizing metrics to drive optimization efforts. Iβm motivated by the challenge of creating ultra-reliable systems that safeguard client assets and user data.
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Google India
Built an AI-powered video analytics system that automatically detects, classifies, and timestamps airport turnaround events (aircraft arrival β servicing β departure) from raw CCTV feeds. π Business Impact: βοΈ Eliminates manual logging of turnaround processes. β± Provides precise operational KPIs (on-time performance, delays, resource usage). πΈ Helped the client secure $1M+ in funding by showcasing efficiency improvements. π Currently being piloted for deployment at airports in India. π Video shows live event detection from CCTV footage; right shows the event Gantt chart timeline output.
π Built for a freight forwarders & customs brokers to automatically categorize extracted form data into business-specific buckets (e.g., renewal, claims, endorsements). π Impact: π Eliminates manual sorting of documents. β± Reduces SLA turnaround from hours β minutes. π Cuts operational overhead dramatically. π Provides structured, business-ready datasets for analytics & AI tasks. Attached is a screenshot of the final deployed pipeline.
π Built for an insurance company to replace tedious manual parsing of proposal forms. Earlier: π©βπ» Several data-entry professionals manually keyed in details. Now: β Just one verification employee reviews the OCR output. πΈ Massive cost savings + faster processing. β¨ Impact: β± 80%+ time saved π Operational costs slashed π Reliable, scalable, and ready for bulk processing Attached image shows the transformation: form β structured results.
Bachelor of Technology (BTech) in Information Technology
2018-01-01-2022-01-01