Vishal M.

• Leading integration of Numbers Station technology into Alation's $1.7B enterprise platform, working directly with CEO • Scaled WAU by 10X and developer adoption by 6X by iterating rapidly on customer feedback and usage patterns • Driving $XXM+ quarterly revenue through deep customer engagement and enterprise deal execution • Leading infrastructure decisions for multi-tenant deployment across diverse enterprise environments

Acquired by Alation for $XXXM – CB Insights Top 100 AI Companies 2024 • Built 0→1 product translating academic text-to-SQL research (Prof. Chris Ré) into enterprise-ready platform • Embedded with customers to define requirements; established CS & Pre-sales with 170% retention, +75% conversion • Led cross-functional team of Stanford/UW PhDs and engineers shipping unified agentic framework • Developed NSQL models outperforming GPT-4 (66% vs 42% accuracy) at 250× smaller size for on-prem deployment • Championed open-source strategy: 3K+ downloads, 585 GitHub stars, adopted by MotherDuck, Ollama, LlamaIndex • Made infrastructure tradeoffs balancing model size, latency, and enterprise security requirements

• Bootstrapped AI Center from 0→1; launched Document Understanding generating multi-million dollar revenue • Led technical evaluation of 50+ AI startups → $52M acquisition of Re:infer; managed post-acquisition integration • Designed pricing strategy from customer usage data and COGS analysis; expanded GTM with field teams

Reporting to Dr. Richard Socher, Chief Scientist • Built 0→1 voice AI product from applied research; demonstrated by CEO Benioff at Dreamforce (340K+ attendees) • Invented multi-tenant AI architecture (Patent #11,769,013) reducing customer deployment time by 50% • Invented async state management for high-frequency systems (Patent #11,048,684) cutting load times 30% • Led 3 agile teams (engineers, data scientists, designers); drove 24% ACV growth and 4× API adoption Product Demos : Low Code : https://www.youtube.com/watch?v=9spxeRJ2BRU Einstein Assistant : https://www.youtube.com/watch?v=XGROwGFi8Og Einstein Bots : https://www.youtube.com/watch?v=neuF2tSeqO8

• Worked on modeling sequence of bike share trip patterns to predict demand of bikes at different locations in NYC • Experimented with trigonometric periodic pattern extractors to increase the accuracy and account for weather related impact • Experimented with having monte carlo approach to optimize non convex function

• Implemented dark launch framework for micro services thus providing ability to manage exposure of new features to clients • Provided architectural basis for 50% performance enhancement by analyzing redundancies in routing decisions, web services calls (SOAP, Thrift, REST) and Tier/Node inter-dependencies (AppDynamics)

Contributed in timely incremental Scrum releases of the product ‘H20’, a sales force application with 500+ users Formulated demographic, periodic and designation based analysis of employee competition and cumulative and individual calls/sales on a multi-schema and recursively architected PgSQL database for the application Implemented caching and REST architecture solution for the same using EJB and Android sdk, it served as one of the key features to attract clients

Key Courses: Statistical Natural Language Processing, Machine Learning and Computational Statistics, Computer Vision, Deep Learning (Yann lecun), Web Search Engines