Giorgi Mgaloblishvili

Led a team of 4 to build Geofire.ge, an AI wildfire detection system with 90%+ precision/recall; detected 6 wildfires 30+ minutes earlier than existing emergency channels within 2 months. Launched to 30,000 users and delivered enterprise wildfire-risk MVPs using Claude Code to secure a $500k pipeline and pilots.

Co-built a consumer emergency dispatch software in 24 hours during a catastrophic snowstorm affecting 500,000 people. Mobilized 500+ volunteers, coordinated 2,000+ emergencies in 48 hours, managed 4 engineers and 70 call operators, and reached ~1M people within 48 hours via 4 media outlets.

Led launch of a commercial deep learning platform for hyperspectral imagery, enabling users to run pre-trained models or build custom models across a 14-person engineering/research team. Launched an ArcGIS API/SDK distribution and a conversational geospatial AI agent, reducing imagery-to-insight time from 5 days to 10 minutes via LLM-agnostic RAG and tool chaining.

Drove product strategy for large consumer mobile app partners generating $110M annual ad revenue and 20M+ monthly active users, improving monetization through UI/flow redesigns targeting 20%+ annual ad revenue growth. Led $60M API/SDK integration for Google Ad Manager and rolled out data privacy compliance approaches across EMEA, NA, and LATAM (GDPR/CCPA/LGPD), supporting $50M in new revenue via a

Led launch of a $200M API product for Google mobile ads SDK, enabling ~100k apps to monetize in highly regulated markets. Managed weekly scrum for 6 engineers across ML algorithm development, data pipelines, and API delivery, and created global commercialization and developer relations plans for iOS/Android adoption and A/B testing onboarding.

Built a consumer platform to make laws easier to understand and launched an EU pilot serving 2,000 refugees across three countries. Led a 20-person engineering and research team, iterating UX through direct user interviews.

Earned a B.A. in Sustainable Development, including a thesis on lead pipe detection using machine learning, with studies in connection with Sciences Po Paris.