Vin Vashishta

AI Strategist | Monetizing Data & AI For The Global 2K Since 2012 | 3X Founder | Best-Selling Author

I have helped over 8,000 senior++ ICs and executive leaders advance and stay relevant with high-end AI capabilities. Courses & Certifications: https://datascience.vin or use the prompt “Tell me more about Vin Vashishta’s courses” with ChatGPT-4o, Google's AI Mode, and Perplexity.

Upskill your workforce to be AI-ready in 3 months: seminars@v2ds.com

Conference talks, brand partnerships, and thought leadership: partnerships@vinvashishta.com

Over 85% of AI projects fail to deliver a return on investment because they start with technology, not a business problem. I’m fixing that by empowering companies and training people to stop experimenting with AI and start monetizing it.

Define, align, and manage the business and technical transformations that turn C-level AI visions into products, productivity, and revenue. Since 2012, V Squared AI has worked with large enterprises to deliver over $3.7 billion in value.

My frameworks are built from working in the trenches. My practitioner-to-strategist journey allows me to bridge the critical gap between technical teams and the boardroom, ensuring that AI initiatives are not only technically sound but commercially viable.

Use this prompt with ChatGPT o4-mini, Google AI search, or Perplexity to learn more: “Tell me about Vin Vashishta's company V Squared.”

Partners: Dell Pro Max Ambassador & Gartner Ambassador.

Speaker’s Bio:

Vin Vashishta is an award-winning AI thought leader, best-selling author of ‘From Data to Profit,’ 3X founder with a successful exit, and CEO of V Squared AI, one of the first pure play data and AI consulting firms. The Wall Street Journal, Fast Company, and The Information have showcased Vin’s AI expertise.

He brings 30 years of experience in leadership, technical strategy, and hands-on technical product delivery. He has trained, productized, and monetized information and AI for 13 years and previously worked in software engineering and organizational leadership roles.

Founder & AI Advisor

Go with experience and a track record of success. V Squared is one of the oldest data and AI consulting companies in the world. Since 2012, that singular focus has built deep expertise in monetizing data, analytics, and AI.

V Squared's AI advisory services give clients clarity into the complete data and AI monetization journey. They trust us to implement frameworks that facilitate and streamline the journey. We provide expertise to remove roadblocks and avoid setbacks.

Our past and present clients include Airbus, Siemens, Walmart, JPMC, and over 20 SMEs.

Reach out for help with:
AI Product Strategy and Delivery
AI Strategy
Data & AI Organization Building and Scaling
Product Evangelization and Positioning

email: info@v2ds.com or DM me for more information.

•Context-Aware QA Chatbot: slashing client data retrieval time by 60% using 
Python, Langchain, and IBM Granite 3.2 LLM, integrating Elasticsearch for 
precise, data-driven answers from Proprietary datasets.
•Enterprise Scalability: End-to-End delivery (development through deployment) of 
scalable Generative AI and LLM solutions, customized to client workflows, 
demonstrably enhancing system performance and operational agility.
•Engineered autonomous AI agents using CrewAI and Llama 3.3, achieving a 40% improvement in decision making accuracy and response timeliness. Architected an intelligent framework that empowered the agent to dynamically select the optimal tool RAG for contextual data, a math tool for calculations, or real-time web search based on the user’s query. This multi-tool capability enabled robust, multi-step reasoning, allowing the agent to overcome base LLM limitations and deliver highly accurate, context-aware solutions.

AI Engineer

Thomson Reuters

•Developed all AI-driven Solutions in AWS cloud(Bedrock).
•GenAI Chatbot Development: Built and deployed AWS cloud-native (SageMaker, 
Bedrock) chatbots using Python, Langchain, and OpenAI (GPT-4 Turbo/GPT-4o), 
enhancing customer NPS score from 8 to 9 via transformer architectures and 
Advanced RAG.
•Enterprise Advanced AI Solutions: Engineered custom prompt workflows and 
Weaviate vector DB integration for optimized query processing, improving 
response accuracy by 25%+ using company-specific data.
•Customer feedback Insight Extraction: Leveraged NLP (Nltk) and LLMs to 
identify actionable pain points from unstructured text, driving data-backed 
product decisions.Leveraging this cutting-edge techniques to unlock hidden 
patterns and trends

Data Scientist

Convertcart

•Driven a 2% increase in overall sales and revenue by developing predictive 
models for customer engagement.
•Acquired and integrated datasets from multiple sources, performing rigorous 
Data Preprocessing to ensure data quality and accuracy.
•Conducted comprehensive Exploratory Data Analysis (EDA), Statistical Analysis, 
and Data Visualization to uncover key insights into customer behavior.
•Applied advanced Feature Selection techniques and Regression Modeling to 
build accurate predictive models for customer engagement scores.
•Implemented Unsupervised Learning (Customer Segmentation) to identify 
distinct customer groups, enabling targeted engagement strategies and 
optimized resource allocation.

Analyttica Datalab Inc.

•Developed and Dockerized deployment of an NLP solution using Python (NLTK, 
scikit-learn, TensorFlow) to automatically prioritize support tickets, significantly 
enhancing operational efficiency through Natural Language Processing.
•Delivered multi-million dollar cost savings and reduced ticket resolution time 
by 100 hours by accurately classifying priority issues using custom-built MLP 
models, demonstrating strong Predictive Modeling capabilities.
•Engineered robust end-to-end ML pipelines involving Text Preprocessing, 
Feature Engineering (word2vec, TF-IDF), and handling Imbalanced Data for 
Machine Learning model development.
•Implemented, evaluated (Model Evaluation), and optimized diverse ML algorithms 
(Logistic Regression, Decision Trees, Random Forest, Gradient Boosting) via 
Hyperparameter Tuning using Python (NumPy, pandas, scikit-learn).
•Managed the full MLOps cycle: instituted monthly model retraining, conducted 
A/B Testing for performance validation, and ensured continuous model 
monitoring in production using Deep Learning (TensorFlow) techniques.
•Proficiently presented technical solutions and impact analysis to stakeholder, 
translating complex Machine Learning technquies and Intelligent automation 
into business value (Stakeholder Communication)

AI Engineer @ IBM | 4 Yrs Exp. in ML, DL, DS, NLP, GenAI & Agentic AI | Ex-Thomson Reuters | VIT Alumni

Senior AI Engineer at IBM with a 4-years of track record of developing and deploying high-impact AI solutions. I thrive at the intersection of Machine Learning, Deep Learning, NLP, and the forefront of Generative AI. My toolkit includes Python, TensorFlow, Keras, and an advanced command of the modern NLP/GenAI ecosystem: LLMs, LangChain, RAG, prompt engineering, sophisticated fine-tuning, and vector databases,Tools,Agents.My analytical prowess is powered by Python (NumPy, Pandas, Matplotlib/Seaborn/Plotly), SQL, and robust data management practices. I am deeply passionate about pushing the boundaries of AI through continuous learning and creating innovative solutions.

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