LattIQ

?? ??????-????????: ?????? ??????’?? ???????? ???????? ????????—?????? ???????? ?????????????? ???????? ????????????????. Data is everywhere. But here’s the challenge: It’s fragmented, unstructured, hard to trust, and underutilised. While most organisations ???????? data, few know how to ???????????????? it. Even fewer know how to ???????????????????? it. ?? What if data wasn’t just shared, but curated, packaged, and activated—like a product? ?? ?? What if raw, scattered data from multiple sources could seamlessly plug into business workflows—without compliance risks, friction, or endless integrations? ?? This is ???????? ???? ?? ?????????????? (????????)—a ??????-??????????, ????????-?????????? approach to unlocking alternate data for real-world impact. It’s a new way for businesses to think about data monetization, collaboration, and strategy. It’s not just about accessing data—it’s about making it work, securely and compliantly. ?? ???????????? ???????? ????????????????: ? Why ?????? ???????? ≠ ???????????????? ?????????? ? How to ???????????????? ???? ???????? with minimal friction ? The future of ????????????, ???????????????? ???????? ?????????????????????????? From retailers like Amazon, Walmart, Target to payment networks like Revolut, PayPal, Chase, Mastercard and even consumer ecosystems like Truecaller, Foursquare, the biggest players are building data assets for consented, compliant and high-trust intelligence. ? The data economy is evolving—are you driving it or catching up? #DaaP #DataProduct #DataCollaboration #FutureOfData #PrivacyFirst

?? LattIQ????? ?????? ??????/?????? ??????????:???????? ??????????????????!??? ???????????????????? ???? ?????? ?? ??????????????????; ????’?? ?? ??????????????- As the data collaboration platform of choice for consumer tech giants, enterprises, and financial services customers, we are committed to security, resilience, and privacy-compliant data collaboration. This certification is just the beginning. While there’s much to be done—supporting comprehensive #SecurityControls, custom activation channels, and advanced Privacy-Enhancing Technologies (#PETs)—this marks the first step toward building a platform that meets global standards for our customers, data, and integration partners. At LattIQ, we are shaping the future of secure and compliant data collaboration—one step at a time. ?? Huge shoutout to Team Ofofo for a seamless audit and certification ?? #DataCollaboration #PrivacyFirst #ISO27001 #LattIQ #Security #Compliance #PrivacyEnhancingTechnologies #GlobalStandards

Did you know your ?????????? ???? ?????????????? wasn’t always recognized as a fundamental right in India? As Nandan Nilekani, often hailed as India’s CTO, famously predicted, ?????????? ?????????? ???????????? ????????-???????? ???????????? ???? ?????????????? ???????????????????????? ????????. This profound truth lies at the heart of the #DPDPA, a law that is a balancing act between data protection and empowerment through data. From its historical journey to the practical implications for individuals and businesses, this article unpacks everything you need to know about India’s new Privacy law. ?? Curious about what makes DPDPA a game-changer for the digital ecosystem? Click to dive in! #DataPrivacy #PrivacyLaw #DataProtection #DataEmpowerment #India

???? ???? ???? ????????????????????, ?????? ?????? ???????? ?? ?????? ???????????????? ????? ?? This has been a common theme in most of our conversations with enterprise leaders trying to improve their workflows using AI, making AI one of the most exclusive technologies in spite of all the hype. The answer lies in the key pillars that define AI development. The AI landscape stands on 5 critical pillars, but not all are equally robust. Here's a breakdown of the paradox that's shaping all of our futures: ?? ???????????? ??????????????????????: ??. ????????????????: Contributions from collaborative public projects and a vibrant community fosters continuous evolution of open-source learning frameworks removing barriers of licensing or resources. LLaMA from Meta is a prime example of how high-performing models are increasingly being shared with the public. ??. ??????????????????????????: Chat, voice, and user-friendly APIs have made AI tools accessible to 100s of millions worldwide. People no longer need specialized technical skills to leverage AI’s capabilities in their day-to-day lives. ?? ??????????? ???? ????????????????: ??. ????????????????????????????: GPUs are widely available today across cloud platforms. Despite this convenience, hardware is still dominated by a handful of companies, exposing AI compute resources to geopolitical influences and potential supply chain disruptions. ??. ????????????????????: AI ethics is under intense global debate, with different regions proposing varied regulations and standards. The EU has taken a lead role through its AI Act—signaling where global policy may be heading. ?? ?????? ???????? ??????????????????: ??. ???????? a. ???????? ?????????????????? remains a key obstacle. A few major players possess the most comprehensive, high-quality datasets, while everyone else struggles with siloed, unstructured, or insufficient data. To train state-of-the-art models, we need to come together—creating a critical mass of clean & diverse data through consortiums and privacy-first platforms. b. ?????????? != ????: While most GenAI excel at content creation, they are less reliable for decision-critical applications like personalization, risk assessment, forecasting, etc. Clean, Diverse and Fresh Proprietary datasets are not just a resource but a cornerstone for building predictive and prescriptive models crucial for high-stakes decision-making At ????????????, we’re focused on solving the data puzzle. We believe AI shouldn’t be reserved for the few. That’s why we’re exploring ?????????????????????????? methods that let organizations benefit from each other’s data without actually sharing or losing control of it. Our goal? Level the playing field and make responsible data access as seamless and equitable as the rest of the AI stack—so developers everywhere can move from merely using AI to shaping it.

Last month, Team LattIQ & friends participated in #BuildAAthon2024 by Sahamati, an innovation-focused hackathon aimed at advancing the Account Aggregator (AA) framework in India. Competing under the track “???????????????????? ?????????????????? ???? ???????????????? ?????????? ?????????????? ????????????????????”, we proposed transformative changes to AA to elevate the vision of DEPA (Data Empowerment and Protection Architecture). ?? ?????? ?????? ?????????????????????? 1?? Privacy-First Intelligence Transfer: ???????????? ???????? ???????????????? ?????? ?????? ???????? ?????????????? ?? By shifting inference cycles upstream to Financial Information Providers (FIPs), we mitigate uninformed consent risks & safeguard sensitive data at its source. This redefines AAs as consented intelligence-sharing frameworks rather than mere data-sharing mechanisms. 2?? Custom Scoring & ML Models: ???????????????? >> ?????? ???????? ?? FIUs can deploy bespoke ML models tailored for fraud detection, credit assessment, or other custom needs. By leveraging observed user behavior as training data, AA can move beyond static rule-based checks to enable dynamic, AI-driven insights. 3?? Integration of Non-Financial Data: 360 ???????????? ???????? ???????????????? ?? Expanding the AA framework to include data from telcos, payment networks, e-commerce, consumer tech, & government agencies. This enables richer personalisation & risk assessment, secured by federated learning & Privacy-Enhancing Technologies (PETs). ?? ???????????????? ?????? ???????????? ???? ???????? ?????????????????????????? Our solution could transform the AA framework into an interoperable intelligence-sharing platform, leveraging PETs to bridge financial and non-financial data for impactful use cases like: ? Credit Access: Enhance gig workers’ inclusion ? Fair Insurance: Data-driven premium personalization ? Risk Models: Leverage telco, consumer tech and payments data ? Fast Financing: Government-based asset verification ? Digital Records: Privacy-first unified repository of digital footprint ?? ?????? ?????????????????? ???????? ?????? ?????????????????? The judges included leading operators, policy makers, and industry leaders who patiently brainstormed with us on how this could be a reality. Sharing some of our biggest takeaways: ?? Data & Privacy Literacy: Raising awareness across the ecosystem ?? Policy Incentives: Encouraging multi-regulatory collaboration under a unified data framework ?? Technical Advancements: Building decentralized infrastructure to support scalable, privacy-first solutions We’re immensely grateful to Sahamati for creating this inspiring forum! Together, let’s redefine data collaboration in India! ?? ?? Watch our Full Presentation from the final round: [Link in Comments] Team LattIQ: Hardik Katyarmal | Akash Rathi | Jaydev Sirmukaddam | Gunasekaran Namachivayam | Akshay Srinivasan CC: Sahamati #Sahamati #AccountAggregator #DataPrivacy #DataEmpowerment #LattIQ

Here is an excerpt from one of Apple's Privacy Docs:? ?????????? ?????? ???????????????????? ?????????? ?????????? ?????? ?????????????? ?????? ???????? ???????????????????? ???? ?????????????? ?????????????? ???????? ???????? ???????? ???? ?????? ?????????? ?????? ??????????, ?????? ??????????????: ???????? ?????? ?????????? ?????? ???????????????? ?????? ?????????? ???????? ?????? ???????? ???????????????? ??????????????????????? ???????? ???????????????? ???????? ???????????????? ???????? ?????????? ???????????? ?????????????? ????????? ?????????? ?????????? ?????? ???????????? ???????? ??????????? ?????? ?????????????????? ???? ???????? ?????? ???????? ?????????? ?????????? ?????????? ?????? ?????????????? ???? ?????????? ??????????????????—???????? ???? ???????? ?????? ?????????? ???????? ???? ?????????? ??????????????????—???? ????????????????.? ? In our hyper-connected world, the demand for impactful insights often competes with the need for privacy protection. Differential Privacy (DP) bridges this gap by ?????????????????????? ?????????????????? ???????????????????? “??????????” ???????? ????????, safeguarding individual identities while preserving the value of analytics. This innovative approach is redefining privacy in fields like machine learning, government data, and consumer insights, offering stronger guarantees than traditional anonymization methods.? ? In our latest blog, explore how DP is setting new standards for privacy-first data analysis without sacrificing utility. Our post covers:? ? ?????? ???? ??????????: A systematic method to protect identities while ensuring data remains useful.? ? ?????? ????????????????????????: Transforming privacy practices in areas like machine learning and consumer insights.? ? ?????? ???? ???????????? ??????: Providing stronger privacy guarantees than traditional anonymization.? ? Discover how DP is elevating privacy standards in data analytics and machine learning: https://lnkd.in/gF2u-zaN ? #DataPrivacy #DifferentialPrivacy #PrivacyTechnology #DataProtection #PrivacyInnovation

?? This festive season, let's celebrate smarter decisions for brighter outcomes. May the festival bring prosperity, joy, and the spark of new possibilities into your life. ? Warm wishes for a bright and meaningful Diwali from all of us at LattIQ! ?? ??

Retail Media has established itself as the fastest growing advertising category (+21% YoY) overshadowing even paid social and paid search as of 2024. So what is the hype about? Why is it outperforming other channels, drawing over $54 Bn in marketing budgets worldwide? In this post, we dive deeper into how the rise of Retail Media Networks is transforming many businesses into powerful media houses and what's the secret behind its performance.

??????? ???? ?????? ?????????? ????????????? ??????????????? ????????????? ???????????????????????? ???????? ??????????????? For years, people have thought of?data privacy?and?utility?as opposites—an impossible trade-off to choose between protecting personal information or getting useful insights from data. The prevailing belief, especially in ecosystems driven by data "sharing" stems from a long-standing binary approach: either share data freely, or protect it by keeping it siloed and losing potential insights. But the game is changing. Privacy-Enhancing Technologies (PETs)?are flipping this narrative by unbundling these concepts and quantifying privacy budgets. PETs such as?Differential Privacy (DP), Federated Learning (FL)?and?Secure Multi-Party Computation (SMPC)?are challenging the notion that privacy and utility are binary choices. These PETs rely on advanced cryptography and quantitative mathematics, making it possible for multiple parties to analyse?distributed datasets without the data ever leaving its source, thus uprooting the idea of data sharing to drive utility. Keep useful data Private and private data Useful. No more trade-offs. Just possibilities.

?? We’re excited to announce that the?LattIQ?website is now LIVE! ?? At LattIQ, we’re unlocking the power of secure data collaboration to help businesses turn?collective intelligence?into actionable insights. Our platform unlocks alternate proprietary data, providing access to unique signals that fuel innovation. ?? Whether you’re in AdTech, FinTech, or Commerce, discover how our data collaboration tools can?elevate your decision-making?and supercharge your workflows. Visit us at www.lattiq.com to learn more about what we do and how we’re reshaping the future of data collaboration! #DataCollaboration #LattIQ #WebsiteLaunch #CollectiveIntelligence