Sumit Ranjan

As Co-founder & CTO at Emvo, I lead the end-to-end strategy, architecture, and engineering behind our sovereign AI Brains — high-performance, domain-trained LLMs purpose-built for secure, enterprise agentic systems. My work focuses on building AI infrastructure that enterprises can fully trust: • Sovereign AI Brains that are private, controllable, and fine-tuned on domain-specific data • Agentic AI systems designed with reliability, transparency, and verifiable decision-making • AI Security & Governance baked into the stack from day one — not an afterthought • Model safety, red-teaming, and secure deployment aligned with global Responsible AI standards • Scalable AI platforms that support real-world workloads with speed, auditability, and performance • End-to-end architecture for enterprise adoption: data pipelines, training, evaluation, deployment, and monitoring I work closely with product, research, and engineering teams to turn complex enterprise problems into robust AI systems that can operate safely at scale. My focus is simple: Build AI that enterprises can trust, control, and rely on.

I guide strategic growth and maturity of the platform by shaping its architecture, agent workflows, and adoption strategies. My role includes advising on Agentic AI architecture, enterprise integration, and product innovation, ensuring scalability and alignment with industry best practices. I collaborate with the team to refine features, enhance usability, and foster partnerships, driving impactful adoption in real-world enterprise deployments.

This course explores how AI is driving digital transformation across industries. Participants will learn: - The strategic role of AI in shaping business models and operations - Frameworks for assessing and improving AI readiness - Best practices in data, technology, and talent enablement - Case studies of organizations leveraging AI for growth and innovation Designed for leaders and professionals, the course bridges business strategy and emerging technologies, equipping you to lead successful AI-driven transformations.

As an Advisor at Protect Neuron, I help enterprises across the UAE strengthen the security and governance of their AI systems. My focus is on ensuring that organizations adopt and scale artificial intelligence responsibly — balancing innovation with safety, ethics, and compliance. Key Responsibilities AI Security Advisory: Guide client organizations on securing AI models, data pipelines, and generative AI systems against adversarial and insider threats. Responsible AI Governance: Help enterprises design and implement responsible AI frameworks covering fairness, transparency, accountability, and explainability. Risk and Compliance Management: Assess AI systems for regulatory compliance, including UAE’s AI policies and international frameworks such as NIST AI RMF, EU AI Act, and ISO/IEC 42001. Model Protection Strategy: Advise on technical safeguards for protecting model weights, training data, and prompts from exfiltration or misuse. AI Innovation Enablement: Support clients in safely integrating GenAI tools and LLMs into their workflows while maintaining data privacy and trust. Training and Awareness: Conduct workshops for executive and technical teams on AI risks, governance practices, and secure innovation strategies. Collaboration and Influence: Partner with CISOs, data leaders, and regulators to build a secure AI adoption ecosystem across industries in the UAE.

• Collaborated with the OWASP GenAI Project Group to identify and research threats associated with Agentic Systems. • Contributed to key initiatives such as the “Landscape of Agentic AI Security & Governance” and “Agents System Top 10.” • Engaged in discussions and strategies to enhance security measures in Agentic AI systems.

There is a saying ” When one finds the true Guru, one can conquer half the world”. Neural Network Guru is a community-based data science portal for data science enthusiastic. The main objective of the portal to share the best and easy data science learning resource. There are lots of websites exists for learning data science, but we came up with unique approach of learning data science. This website consists of various blogs, flashcards, webinars, and case studies on data science.

As the Head of Responsible AI, the role involves leading the development and implementation of comprehensive strategies to ensure the ethical, secure, and transparent deployment of AI technologies. The mission is to champion responsible AI practices that align with organizational values while safeguarding users and stakeholders. This position requires close collaboration with cross-functional teams to identify, assess, and mitigate risks associated with AI systems, ensuring robust security frameworks are in place. By fostering a culture of accountability and ethical awareness, the role empowers teams to innovate responsibly, balancing cutting-edge advancements with societal and organizational well-being. Through ongoing research, proactive risk management, and stakeholder engagement, the focus is on shaping a trustworthy AI ecosystem that prioritizes fairness, transparency, and safety. The work not only drives innovation but also ensures that AI technologies are developed with integrity and a focus on long-term positive impact.

• Leading Generative AI and LLM innovation initiatives at Majid Al Futtaim Carrefour, deploying advanced GenAI tools on Linux systems. • Implemented open-source LLMs (Mixtral, LLama) to build enterprise-level GenAI solutions. • Developed a RAG-based solution to support Category Management, delivering actionable product insights for product rationalization. • Created a RAG-based pipeline for a multimodal Generative AI system to analyze leaflets, optimizing competitive pricing and promotional analytics.

• Developed and deployed Deep Learning models for retail analytics at Carrefour, driving insights and efficiency in operations. • Led the development of various AI tools to support Category Management projects, enhancing decision-making and optimizing product management strategies.

Delivered a comprehensive Generative AI curriculum covering foundational to advanced concepts. Topics included: - Evolution of AI: From Bag of Words → TF-IDF → Word2Vec → RNN → LSTM → Transformers → BERT. - Generative AI Models: Architecture, principles, and real-world applications. - Hands-on Implementation: Practical exercises using Python and AI frameworks. - Industry Use Cases: AI in content generation, conversational agents, recommendation systems, and enterprise solutions. Key Outcomes for Students: - Built understanding of AI model evolution and underlying mathematical principles. - Implemented real-time GenAI projects and explored enterprise applications. - Gained practical skills to bridge theory and industry-ready solutions.

MResult Corporation is a End-to End Data Management services firm that specializes in Business Intelligence, SharePoint Portals, Software Development, and Data Analytics that help companies plan, build and manage solutions designed around their missions, goals and people rather than specific technologies. Role and responsibilities: ► Work is related to AI Application development, Machine learning, Natural language processing and Language Models. ► I work for Decision Science Team at MResult and lead multiple Natural language processing health care domain projects. ► Working on various cutting-edge natural language processing problem using BERT, NLTK, SPACY, PyTorch, Keras.

VMware, Inc. is a publicly traded software company listed on the NYSE under stock ticker VMW. Dell Technologies is a majority share holder. VMware provides cloud computing and virtualization software and services. It was one of the first commercially successful companies to virtualize the x86 architecture. Roles and Responsibilities: ► Work is related to AI Application development, Machine learning and Natural language processing. ► Leading SEO Analytics project at VMware. ► I work for the data science and advance analytics team of Global Service Support(GSS) at VMware. ► Working on various cutting-edge natural language processing problem using BERT, NLTK, SPACY, PyTorch, Keras. ► Leveraging Unstructured Information for Google Search query data using Natural language processing. ► Developed a python package for SEO Analytics which helps to analyze google search console data

Machine Learning certification by Massachusetts Institute of Technology

Designing frameworks to secure AI agents and GenAI systems against evolving cyber threats while embedding accountability, ethics, and trust. Key Focus: 🔹 Responsible AI Framework Development: Building guardrails for AI agents (autonomous systems) and GenAI applications to mitigate risks like bias, misuse, and unintended harm. 🔹 AI Security for Agentic Systems: Protecting LLM-powered agents and generative models from adversarial attacks, data poisoning, and prompt injection vulnerabilities. 🔹 Cybersecurity for GenAI: Securing AI-generated outputs, APIs, and multi-agent workflows against exploitation in enterprise environments. 🔹 Ethics-by-Design: Embedding transparency, fairness, and human oversight into AI agent architectures to align with global AI regulations (e.g., EU AI Act).

Executive Development Programme (EDP) on Data Privacy & AI: Law, Policy and Practice at Dhirubhai Ambani University – School of Law, in collaboration with the Indian National Association of Legal Professionals (INALP). The programme provides a comprehensive understanding of data protection laws, global privacy regulations (GDPR, CCPA, PIPL), and AI governance frameworks including the EU AI Act. It combines live sessions, case studies, and interactive simulations to build practical skills in Data Protection Impact Assessments (DPIA), Fundamental Rights Impact Assessments (FRIA), and AI Governance Impact Assessments. With sectoral applications in FinTech and Healthcare, and a capstone project to design a data privacy and AI governance roadmap, the programme prepares professionals to address real-world regulatory and ethical challenges in the digital economy.

Birla Institute of Technology & Science, Pilani is a private institute of higher education and a deemed university under Section 3 of the UGC Act 1956. The institute is one of the first six institutes to be awarded the Institute of Eminence status in 2018. Program has the same curriculum as of the full-time courses, with classes over the weekend. The program is one of the most comprehensive Masters degree programme in the Data Science and Software Systems without taking a break from your career. M.Tech. Data Science and Software Systems is a four-semester program designed for working professionals that helps learners build mathematical and engineering skills required to advance their career as a Data Scientist.

This 7-week short course was offered primarily as an on-campus (physical) event. Below things are taught as part of the course: 1. Train models to achieve state-of-the-art results in computer vision, natural language processing, tabular data and prediction, and recommender systems 2. Turn your models into web applications and deploy them 3. Understand why and how deep learning models work, and use that knowledge to improve their accuracy, speed and reliability 4. Select the most appropriate deep learning techniques for given problems 5. Implement neural network training methods from scratch 6. Reflect on the ethical implications of your work - to ensure you’re making the world a better place with your skills

Awarded Silver Medal in field of Electronics & Telecommunication Engineering.