Chetan Rane

BISHAL SINGH Ayushman Johri Kashish Verma Abhinav Bhushan Big Data Fails Without “Right Data” More data does not mean better decisions. The documents highlight a critical shift: move from data to decisions → decisions to data  Survival bias, irrelevant variables, and poorly framed questions can mislead even the most advanced models. That’s why many AI initiatives underperform. What works instead? Start with the business question Define the decision that matters Then identify the data and model required Use cases: churn reduction, credit risk, operational efficiency Possible solutions: hypothesis-led analytics, decision frameworks, model governance At Truverizen, we design AI systems that serve decisions — not dashboards. #RightData #Analytics #AIAdoption #TruverizenTechnologies

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Raghunandan Mishra, VP, AI and Data Engineering, 𝐃𝐞𝐦𝐚𝐧𝐝𝐒𝐜𝐢𝐞𝐧𝐜𝐞 at #Agenticon 𝑩𝒆𝒏𝒈𝒂𝒍𝒖𝒓𝒖 𝑬𝒅𝒊𝒕𝒊𝒐𝒏 breaks down the new data governance models required when AI agents generate, curate, and act on their own data, while ensuring provenance and traceability, at #Agenticon Bengaluru Edition. #Agenticon2026 #AgenticonBengaluru #AgenticAI #AILeadership #DataDriven #AITransformation

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Saurabh Jain has been appointed as AVP – AI and Business Analytics at CitiusTech. In this role, he will lead advanced AI, data, and analytics initiatives, driving enterprise-scale adoption of Generative AI, LLMs, and agentic architectures to deliver high-impact digital transformation for global clients. With nearly two decades of experience, Saurabh brings deep expertise from his previous stints at LTIMindtree, EdgeVerve, Infosys, KPIT, Ness Digital Engineering, and Tata Consultancy Services. His strong background in AI architecture, product engineering, cloud platforms, and data-driven systems positions him to play a pivotal role in strengthening CitiusTech’s AI and analytics leadership. 👉Read More: https://lnkd.in/g22FSA2y #saurabhjain #citiustech #avp #ai #business #analytics #ai #data #ltimindtree #edgeverve #infosys #kpit #ness #digital #engineering #tcs #tata #leader #leadershipannouncement

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I am happy to share that the research paper that I co-authored with Deepak Pandey and Vishal Shankar, “𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝘁𝗵𝗲 𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗮 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜”, has been published in SAGE Journals. → https://lnkd.in/gRMFKbBy I want to highlight some of the key contributions and insights that my co-authors and I were able to develop: 𝟭. 𝗖𝗼𝗺𝗽𝗿𝗲𝗵𝗲𝗻𝘀𝗶𝘃𝗲 𝗣𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲 𝗙𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: We identified and deeply analyzed 𝟭𝟱 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹 𝗽𝗿𝗶𝗻𝗰𝗶𝗽𝗹𝗲𝘀 𝘁𝗵𝗮𝘁 𝗳𝗼𝗿𝗺 𝘁𝗵𝗲 𝗯𝗲𝗱𝗿𝗼𝗰𝗸 𝗼𝗳 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜 — from fairness, transparency, and accountability to robustness and privacy. This framework can serve as a reference point for both researchers and practitioners building AI systems that matter. 𝟮. 𝗚𝗮𝗽 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝗮𝗰𝗿𝗼𝘀𝘀 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 & 𝗣𝗼𝗹𝗶𝗰𝘆: We conducted a detailed gap analysis, pointing out where current AI development practices fall short in operationalizing ethical ideals. By bridging that gap between theory and practice, 𝘄𝗲 𝗼𝗳𝗳𝗲𝗿 𝗮𝗰𝘁𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗴𝘂𝗶𝗱𝗮𝗻𝗰𝗲 𝗳𝗼𝗿 𝗳𝘂𝘁𝘂𝗿𝗲 𝗔𝗜 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲. 𝟯. 𝗠𝘂𝗹𝘁𝗶-𝗦𝘁𝗮𝗸𝗲𝗵𝗼𝗹𝗱𝗲𝗿 𝗣𝗲𝗿𝘀𝗽𝗲𝗰𝘁𝗶𝘃𝗲: Our research embraced a multi-stakeholder perspective — considering not only developers but also regulators, users, and affected communities—𝗧𝗵𝗶𝘀 𝗵𝗲𝗹𝗽𝘀 𝗲𝗻𝘀𝘂𝗿𝗲 𝘁𝗵𝗮𝘁 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜 𝗶𝘀 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮𝗰𝗮𝗱𝗲𝗺𝗶𝗰 𝗯𝘂𝘁 𝘀𝗼𝗰𝗶𝗮𝗹𝗹𝘆 𝗴𝗿𝗼𝘂𝗻𝗱𝗲𝗱. 𝟰. 𝗢𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗮𝘁𝗵𝘄𝗮𝘆𝘀: We didn’t stop at principles: we proposed operational pathways — practical processes and governance models — to 𝗲𝗺𝗯𝗲𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗹𝗲 𝗔𝗜 𝗶𝗻𝘁𝗼 𝗲𝘃𝗲𝗿𝘆 𝘀𝘁𝗮𝗴𝗲 𝗼𝗳 𝘁𝗵𝗲 𝗔𝗜 𝗹𝗶𝗳𝗲𝗰𝘆𝗰𝗹𝗲. This includes recommendations for auditing, design reviews, and continuous monitoring. 𝟱. 𝗙𝘂𝘁𝘂𝗿𝗲-𝗙𝗮𝗰𝗶𝗻𝗴 𝗥𝗼𝗮𝗱𝗺𝗮𝗽: Finally, 𝘄𝗲 𝗰𝗿𝗮𝗳𝘁𝗲𝗱 𝗮 𝗳𝗼𝗿𝘄𝗮𝗿𝗱-𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝗿𝗼𝗮𝗱𝗺𝗮𝗽 𝗳𝗼𝗿 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗮𝗻𝗱 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻. We highlight priority areas for the AI community: building tools, establishing governance bodies, and promoting cross-disciplinary collaboration. I hope this paper contributes meaningfully to the conversation around ethical, trustworthy, and socially responsible AI. If you work in AI development, policy, or research, we would like to connect and explore how we can put these ideas into action. Please feel free to share your comments with me. Last but not least, thank you to my co-authors, reviewers, and everyone who supported this journey.

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Snowflake Unveils Cortex AI for Financial Services: Enterprise-Ready AI Built to Scale Read more: https://lnkd.in/dBYi2_fH #IndiaTechnologyNews #Snowflake #CortexAI #FinancialServices #EnterpriseAI #AIBuiltToScale #DataInnovation #FinTech #AIinFinance #CloudData #NextGenAI

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In Episode 11 of Enqurious TV, Mansi Mutreja spoke with @Amit Kumar, Senior Data Manager with 20 years of experience in data engineering, about what actually works in real-world systems. We break down: • Why data ingestion is harder than it looks • When not to build real-time pipelines • Kafka lessons from early adoption • How ClickHouse enables real-time analytics • Cutting ETL costs from $5,000/month to $500/month • Why SQL still wins • AI in engineering: good slave, bad master One key insight: Most teams build for scale before they validate business need. That mistake is expensive. If you're building data platforms or growing in data engineering, this one is practical and battle-tested. Link in comments.

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How can data chaos turn into your organization’s greatest strategic advantage? Arpanarghya Saha, 𝐂𝐡𝐢𝐞𝐟 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐎𝐟𝐟𝐢𝐜𝐞𝐫 at 𝐍𝐢𝐩𝐩𝐨𝐧 𝐈𝐧𝐝𝐢𝐚 𝐌𝐮𝐭𝐮𝐚𝐥 𝐅𝐮𝐧𝐝, reveals the 2025 playbook for mastering data management, boosting forecasting accuracy, and creating a single source of truth. 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐚𝐫𝐭𝐢𝐜𝐥𝐞: https://lnkd.in/gEaFTbtp #IndiaIT360 #DataManagement #DigitalTransformation #TechLeadership #CIOConnect #Forecasting #DataStrategy

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𝐓𝐡𝐞 𝐀𝐈 𝐒𝐨𝐯𝐞𝐫𝐞𝐢𝐠𝐧𝐬 | 𝐄𝐱𝐜𝐥𝐮𝐬𝐢𝐯𝐞 𝐒𝐞𝐫𝐢𝐞𝐬 𝐟𝐨𝐫 𝐀𝐈 𝐋𝐞𝐚𝐝𝐞𝐫𝐬 𝐛𝐲 𝐂𝐗𝐎 𝐋𝐚𝐧𝐞𝐬 Gurudatta Kamath Head of Data & AI at Espire Infolabs, is a seasoned Data, Analytics, and AI leader. Previously, he served as Chief of Data & AI at Navikenz, where he built and led the Data & AI/ML practice and developed purpose-driven AI capabilities. Earlier, he was Practice Head – Data, Analytics & AI at Birlasoft, leading growth strategy, service offerings, solution architectures, accelerators, partnerships, delivery assurance, and practitioner development. He earlier served as Practice Head – Data & Analytics (BFSI) at Tech Mahindra. Prior to that, he was Practice Director – Data Management at Polaris Consulting & Services Ltd. Earlier, he was BI Practice Leader at Zensar Technologies, spent over a decade at Satyam Computer Services Liited (later Tech Mahindra) in consulting and business development roles, and began his career as Assistant Vice President (Finance) at Quantum Financial Services Limited and Audit Manager at Sharp and Tannan. Through The AI Sovereigns, CXO Lanes highlights leaders like Gurudatta Kamath who are advancing enterprise Data & AI transformation. As he notes, “Would be keen to contribute to discuss about how the recent developments in the world of Frontier Model is bringing in opportunities for individuals to develop their own products.” #TheAISovereigns #AILeadership #DataAI #Analytics #CXOLanes

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Read Now: https://lnkd.in/dzHc_P8C Choosing between fine-tuning and contextual input isn’t easy—especially when accuracy, cost, and speed are all on the line. In this blog, our Senior Data Scientist, Alakh Sharma, breaks down when to use each strategy, sharing real-world examples and trade-offs to help you make the right decision for your use case. #AIModelTraining #FineTuning #GenerativeAI #DataScience #AIDevelopment

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Aditya Nair from our Data Engineering team shares how our multi-modal DeepTech platform transforms fragmented data into actionable intelligence—detecting patterns, relationships, and anomalies that drive smarter decisions and proactive risk management. Watch the quick 1 minute video here: https://lnkd.in/gbJqHqrV #ValianTribe #DataEngineering #DeepTech #AIforGood #MultimodalAI #VideoIntelligence

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At AIT Global India, our deep-rooted expertise in data analytics has empowered clients to unlock the full potential of platforms like Palantir Foundry, Tableau, and Power BI. Our team helped a leading manufacturing client transition from legacy systems to a scalable, cloud-based analytical environment—enhancing data accuracy, reducing decision-making time, and streamlining critical workflows. Discover how we’re helping businesses make data-driven decisions faster and smarter: https://lnkd.in/dwP5-NJA #AITGlobal #DataAnalytics #PalantirFoundry #CaseStudy #CloudMigration #ManufacturingInnovation #DigitalTransformation #BusinessIntelligence #AnalyticsLeadership

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Is your job under threat from AI? Three CEOs—Munish Gandhi of Statisfy, Srinath Sridhar of Regie.ai and Amit Aggarwal of Datairis, along with host Eightfold's chief people officer, Meghna Punhani—discuss what's coming and what HR leaders can do now. https://ow.ly/R9BE50VWkNJ #AIInWorkplace #FutureOfWork

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🚌 𝐂𝐡𝐚𝐥𝐨 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞𝐬 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐰𝐢𝐭𝐡 𝐐𝐮𝐚𝐧𝐭𝐢𝐩𝐡𝐢 & 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 Chalo, India’s leading public transport tech company, has teamed up with Quantiphi and Snowflake to modernize its data infrastructure—powering 4B+ rides across 90 cities globally with AI-ready insights, faster data migration, and lower operational costs. With Snowflake’s AI Data Cloud and Quantiphi’s Codeaira GenAI accelerator, Chalo achieved 50% faster data migration and now delivers real-time updates, smarter route planning, and improved customer experiences. 🔗 𝐑𝐞𝐚𝐝 𝐭𝐡𝐞 𝐟𝐮𝐥𝐥 𝐬𝐭𝐨𝐫𝐲 : https://lnkd.in/dJkFCx3q #AIDataCloud #SmartMobility #SnowflakePartner #DigitalTransformation #PublicTransport #GenAI #Quantiphi #SmartCities #FleetManagement #DataDrivenDecisions

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"Ethical AI isn’t a destination – it’s a discipline." As AI systems become increasingly embedded in more decision-making processes, governance shifts from a compliance requirement to a strategic advantage. In a recent interview with CMR, Ashish Heda (Data Science Technology Partner at Tiger Analytics) shares his perspectives on the evolving practice of Ethical AI, diving into: ⬩ Mitigating bias across the AI lifecycle ⬩ Balancing performance and explainability in regulated industries ⬩ The need for robust data privacy frameworks ⬩ Cultural shifts for responsible AI adoption ⬩ Emerging technologies like LLMOps, AgentOps, and AIOps For leaders at the intersection of AI, governance, and impact, the interview offers practical insights on what’s next for intelligent systems and how to get there responsibly. Read the full article: https://lnkd.in/gcNeP4fc #EthicalAI #AIGovernance #ResponsibleAI #BiasInAI #DataPrivacy #TigerAnalytics #LLMOps #AgentOps #EnterpriseAI

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Shireesh Kumar Singh's article reveals how Knowledge Graphs are powering next-gen semantic communication, solving the problem of unknown scenarios through relational reasoning.

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Fractal, the Mumbai-based AI powerhouse, has unveiled Fathom-R1-14B, a 14B parameter open-source LLM that’s making waves with its math reasoning performance surpassing OpenAI's o1-mini and o3-mini, and nearly touching o4-mini—all at a post-training cost of just $499. Available on Hugging Face and licensed under MIT, Fathom-R1-14B scored 52.71% on AIME-25 and 35.26% on HMMT-25, with accuracy jumping to 76.7% and 56.7% respectively with inference-time boosts (cons@64). “This is just a tiny proof of what’s possible,” said Fractal CEO Srikanth Velamakanni, who shared that this effort is part of a larger proposal under the IndiaAI mission to build India’s first large reasoning model, including future plans for a 70B parameter model. Fathom-R1-14B was developed using SFT, curriculum learning, and model merging. A sibling variant, Fathom-R1-14B-RS, trained with reinforcement learning, showed similar results at a slightly higher cost of $967. This launch follows Fractal’s earlier AI healthcare initiative, Vaidya ai, and coincides with Sarvam AI’s release of Sarvam-M, a 24B parameter hybrid model for the IndiaAI mission. India’s open-source LLM race is heating up—and Fractal’s just thrown down the gauntlet.

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