Channel Title: causaLens Channel Description: causaLens is pioneering the world’s first platform for building AI data scientists - empowering everyone to create and deploy their own data science agents in days. As data grows exponentially while data science talent remains scarce, organizations struggle to harness their data effectively. Our platform solves this by enabling organizations to create AI Data Scientists tailored to their specific business context and needs. Teams can collaborate in a multi-agent environment, ensuring human oversight across the entire workflow and making AI-powered data science trustworthy and accessible to everyone – from analysts to business leaders. Seamlessly create and share customized data science agents within a secure environment that protects sensitive information, enabling true enterprise-wide collaboration. A We power industry leaders, including Cisco, Johnson & Johnson, Canon, and McCann Worldgroup, to accelerate and scale their data science capability. <video> Causal AI in BP; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causal AI in BP (BP) Cristiano Da Cruz, Machine Learning Researcher Visit https://www.causalaiconference.com to learn more about upcoming conferences. "Causal AI is already used in the energy sector, but it’s still key for advancing our operations. We use it to quickly turn data into insights and then into actions, which is crucial for managing large operations. We’re looking at how Causal AI is currently used in different parts of the energy industry and how it might be used in the future. We also consider how today’s causal methods are setting the stage for new technologies, including a look at an advanced wind farm concept." #bp #causalens #cai24 #causalai #aiagents #ai </video> <video> causaLens Launches the World's First AI Data Scientists | Build Your Own Data Science Agents Description: The world's first platform to build the world’s first platform for building AI data scientists - empowering everyone to create and deploy their own data science agents in days. Cofounder and CEO of causaLens, Darko Matovski, shares the details in this video. 💡 The Challenge: Nearly 70% of corporate data is never used, leaving trillions of dollars in untapped potential. Traditional data science processes take months, struggling to keep pace with the market’s demands. 🔥 The Solution: causaLens Agent Platform ✅ Pre-built agents: Handle tasks from data cleaning and feature engineering to app building (and everything in between). ✅ Custom agents: Tailored to your organization’s needs and expertise. ✅ Trustworthy Agents: Grounded in your business reality with human oversight at every step. 📈 Early Results: One Fortune 500 company built 50,000 custom models in just one week—a feat that was once unimaginable! 🎯 Empowering Data Scientists: This isn't about replacing data scientists but amplifies their impact. With routine tasks automated, human experts can focus on strategic decisions, creative problem-solving, and governance. They become the Chief of Staff of their own AI workforce! Imagine if everyone in your organization — from Marketing to Product, Supply Chain to Operations —could have a dedicated data science team. Don’t just imagine – you can build your own team of AI Data Scientists in just 5 days. Ready? Head to causalens.com </video> <video> causaLens Agents Platform for Building AI Data Scientists Description: causaLens is pioneering the world’s first platform for building AI data scientists - empowering everyone to create and deploy their own data science agents in days. As data grows exponentially while data science talent remains scarce, organizations struggle to harness their data effectively. Our platform solves this by enabling organizations to create AI Data Scientists tailored to their specific business context and needs. Teams can collaborate in a multi-agent environment, ensuring human oversight across the entire workflow and making AI-powered data science trustworthy and accessible to everyone – from analysts to business leaders. Seamlessly create and share customized data science agents within a secure environment that protects sensitive information, enabling true enterprise-wide collaboration. AI Data Scientists can be created and trained in days, accelerating and expanding business insight and action at an unprecedented scale. </video> <video> Semantic causality and Causal AI; Enabling Discourse for Trust in Real-Time Root-Cause Analysis Description: The Causal AI Conference London 2024 SSemantic causality and Causal AI; Enabling Discourse for Trust in Real-Time Root-Cause Analysis (SLB) Michael Williams, Principal AI Research Scientist Visit https://www.causalaiconference.com to learn more about upcoming conferences. "Counterfactuals enable exploration of solutions in causal-AI. In addition to counterfactual exploration of a causal-AI network, we introduce search-and-summary to provide a rich discourse between the engineer and the AI system. Working in the area of operational risk of non-productive time (NPT), we begin from semantic cause-effect chains from root-cause-analysis. These are interwoven in a primarily knowledge-driven causal-AI structure. Population of a large subset of the initial conditional probability tables is through physics models.That partially trained structure is then refined on scenarios from historical operations and expert-driven hypothetical situations. In deployment a behaviour tree architecture enables a neurosymbolic combination of human and IoT establish the right risk model for the right context. The results are analyzed to identify the key paths through the causal-AI, recovering specific semantic cause-effect chains corresponding to root causes. These are used in two ways: firstly they can be passed for summarization by LLMs, where we use roundtrip verification and access to underlying human-verified text; secondly, the causal-AI result is used in a skyline multicriterion search across the historical and hypothetical cases. We present the details of the complete system and highlight the role that causal-AI plus semantic web can play in enabling discourse on operational risk." #slb #causalens #cai24 #causalai #aiagents #ai </video> <video> Exploring Causal AI Potential in Responsible AI; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causal ML in Practice: Estimating Uplift with Selection into Treatment (PwC, Macquarie Group) Maria Axente, Head of Public Policy & Ethics Ari Cohen, Chief Data Officer Visit https://www.causalaiconference.com to learn more about upcoming conferences. "Join an interesting discussion exploring how causal approaches could reshape responsible AI practices, influence policy decisions, and drive innovation in the financial sector. Drawing from their extensive experience in AI ethics, strategy, and data-driven decision-making, our panelists will offer unique insights into the challenges and opportunities presented by causal AI. This forward-looking conversation will focus on the strategic importance of causal AI and its implications for businesses navigating the complex landscape of AI adoption and implementation – providing valuable insights for professionals across industries." #pwc #macquariegroup #causalens #cai24 #causalai #aiagents #ai </video> <video> Causality in Retail Banking at BBVA AI Factory; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causality in Retail Banking at BBVA AI Factory Álvaro Ibraín Rodríguez, Expert Data Scientist Visit https://www.causalaiconference.com to learn more about upcoming conferences. "In retail banking, understanding the causal relationships between variables is crucial for making informed decisions that enhance customer experience and optimize financial outcomes. At BBVA AI Factory, causal inference techniques are improving our approach to complex challenges where traditional A/B testing is infeasible or removing bias becomes a hard problem. Also, it has significantly enhanced financial health metrics and risk management processes. By utilizing causal inference, we can find out the true impact of various interventions on customer behavior and financial stability, leading to more accurate risk assessments and tailored financial advice. This approach addresses the limitations of conventional experimental methods, which can be impractical or ethically challenging, by providing robust alternative solutions. This presentation will showcase three detailed case studies and quantifiable outcomes, highlighting the practical benefits and advancements that causality offers in retail banking analytics. We will deepen into how we’ve enhanced our recommendation systems and embedded causal inference in our analytics framework at BBVA AI Factory. Attendees will leave the room with a deep understanding of causal AI applications in the financial sector." #BBVA #causalens #cai24 #causalai #aiagents #ai </video> <video> Decoding eCommerce; Facing and solving technical challenges implementing Causal Modeling Description: The Causal AI Conference London 2024 “Decoding eCommerce” – Facing and solving technical challenges implementing Causal Modeling at Bergfreunde.de Alexander Dzionara, Data Scientist Visit https://www.causalaiconference.com to learn more about upcoming conferences. "“Decoding eCommerce” – Facing and solving technical challenges implementing Causal Modeling at Bergfreunde.de” – Find out about the technical challenges (and solutions) Europe’s largest Outdoor eCommerce Retailer Bergfreunde.de (known in the UK as www.alpinetrek.co.uk/) had to face implementing a Causal Model to inform business steering. The focus of this talk will be on exposing the statistical and technical challenges faced, and some of the learnings and solutions implemented." #bergfreunde #causalens #cai24 #causalai #aiagents #ai </video> <video> Causality Upside Down, Aleksander Molak; Causal AI Conference 2024 Description: The Causal AI Conference London 2024 Causality Upside Down Aleksander Molak, Causal ML Tutor / Causal Bandits Host Visit https://www.causalaiconference.com to learn more about upcoming conferences. "When we think about causal modeling, we often focus on (critically important) assumptions necessary to make valid causal inferences. The value of this perspective is hard to overestimate. At the same time, the true goal of applied causal inference is to improve our decision-making rather than just meet causal assumptions. In this talk, we will take a look at a set of methods that allow us to make causal inferences under violated assumptions. Although some, if not all, of these methods might not lead to inferences as precise as we’d like, they can help us solve our real problem – making better decisions." #causalens #cai24 #causalai #aiagents #ai </video> <video> Causality in spatio-temporal graphs; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causality in spatio-temporal graphs (BCA) Robert Nicholls, Head of Data Science Visit https://www.causalaiconference.com to learn more about upcoming conferences. "Graph theory and causal analysis are under-used tools in Data Science in general, but we rarely talk about their data discovery potential. By using these techniques, we were able to discover a cost-saving opportunity in logistics that traditional analysis and ML was unable to identify. In addition, the visually approachable nature of graph theory made the opportunity explainable to business stakeholders. This combination of data discovery and interpretability by a non-technical audience makes causal analysis a uniquely powerful tool for quickly solving business problems that require the cooperation of internal teams." #BCA #causalens #cai24 #causalai #aiagents #ai </video> <video> Causal modelling for social causes, McCann Worldgroup; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causal modelling for social causes (McCann Worldgroup) Gideon Wilkins, Group Head of Research Visit https://www.causalaiconference.com to learn more about upcoming conferences. "In today’s marketing landscape, understanding what drives consumer behaviour is more complex than ever, especially when social causes are added into the mix. In this session, we’ll explore how a leading confectionery brand and McCann Truth Central used causal modeling to find the drivers of brand affinity while also navigating the debates about social cause marketing within the brand team. From taste and value for money to the deeper impact of shared values and social activism, we’ll dive into how causal modelling was used to navigate this sensitive topic and provide compelling ‘what-if’ analysis and evidence to identify growth opportunities worth 5-10% growth in market share." #mccann #causalens #cai24 #causalai #aiagents #ai </video> <video> Causal Inference for Markdown Pricing, Marks and Spencer; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causal Inference for Markdown Pricing (Marks and Spencer) Mindaugas Zickus, Lead Data Scientist Visit https://www.causalaiconference.com to learn more about upcoming conferences. "The dynamic retail environment presents unique challenges for causal inference in optimal pricing. Evolving business tactics, seasonality, changing product assortments, and censored demand create highly contextual, heterogeneous, and time-varying price response effects. In this presentation, we will demonstrate how causal ML is utilized for markdown optimization at Marks & Spencer. We will explain our approach to predicting price elasticities, accounting for uncertainty, and address the pitfalls of using aggregated data for causal inference. Our experiences illustrate how these methods can lead to more robust and effective decision-making processes in complex retail environments." #marksandspencer #causalens #cai24 #causalai #aiagents #ai </video> <video> Leveraging Predictive and Causal AI, TIM; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Leveraging Predictive and Causal AI (TIM) Clara Fabiola Oliva, VP, Data Analytics, Artificial Intelligence & Customer Insight Nicola Vizioli, Strategy and Data Analyst Visit https://www.causalaiconference.com to learn more about upcoming conferences. "The presentation outlines TIM’s strategic approach to harnessing the power of Artificial Intelligence. Starting with predictive AI models that drive customer insights, churn modelling, and operational efficiency, TIM is now advancing towards the next frontier: Causal AI. By integrating causal inference, TIM aims to enhance decision-making, moving beyond prediction to understanding the “why” behind customer behaviour, optimizing interventions, and shaping a data-driven future." #TIM #causalens #cai24 #causalai #aiagents #ai </video> <video> Causality in a real use case in banking; Causal AI Conference London 2024 Description: The Causal AI Conference London 2024 Causality in a real use case in banking (BBVA AI Factory) Clara Higuera Cabañes, Lead Data Scientist Javier Moral Hernández, Senior Data Scientist Visit https://www.causalaiconference.com to learn more about upcoming conferences. "In retail banking, understanding our clients is critical to offering them the best solutions and products. This talk presents an innovative approach based on causality to calculate optimal financial discounts aiming to benefit both the institution and its clientele. Traditional machine learning techniques fall short in this scenario due to the impossibility of making randomized controlled trials and the presence of confounding bias in observational data. We demonstrate with preliminary results on a real use case how causal inference methodologies can overcome these limitations, enabling us to estimate the effect of financial discounts. Our approach allows for interventions and counterfactual analysis, which is crucial for determining personalized optimal discounts. This presentation will detail our end-to-end causal inference pipeline customized for our problem but adaptable to other use cases. It will cover phases like covariate selection, causal discovery, and effect estimation, among others. We will describe our comprehensive approach, including the application and comparison of multiple causal discovery and estimation algorithms. Furthermore, we will contrast the outcomes of our causal inference pipeline with traditional ML-based methodologies, illustrating how causal inference effectively corrects biases that ML cannot address." #bbva #causalens #cai24 #causalai #aiagents #ai </video> <video> Counterfactual Reasoning and What Its Good For- Spotify; Causal AI Conference 2024 Description: The Causal AI Conference London 2024 Counterfactual Reasoning and What It's Good For (Spotify) Ciaran M Gilligan Lee, Head of Causal Inference Lab & Senior Research Manager Visit https://www.causalaiconference.com to learn more about upcoming conferences. "Causal reasoning is vital for effective reasoning in many domains, from healthcare to economics. In medical diagnosis, for example, a doctor aims to explain a patient’s symptoms by determining the diseases causing them. This is because causal relations, unlike correlations, allow one to reason about the consequences of possible treatments and to answer counterfactual queries. In this talk I will present some recent work done with my collaborators about how one can learn and reason with counterfactual distributions, and why this is importantly for decision making. In all cases I will strive to motivate and contextualise the results with real word examples." #spotify #causalens #cai24 #causalai #aiagents #ai </video> <video> The Causal AI Conference London 2024 Highlights Description: Don't miss out on the next Conference! Secure your spot today: https://bit.ly/3C3rXCS cAI brings together experts in Causal AI, including business leaders from renowned brands, data scientists, leading researchers, and academics driven by a shared passion for shaping the future of Causal AI. Engage in thought-provoking discussions, exchange insights on successful implementations and use cases, and learn how the world's largest organizations use Causal AI to drive value. #causalai #causalens #causal #london #ai #conference #artificialintelligence #cai24 #causalaiconference </video>

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Description

causaLens is pioneering the world’s first platform for building AI data scientists - empowering everyone to create and deploy their own data science agents in days.

As data grows exponentially while data science talent remains scarce, organizations struggle to harness their data effectively. Our platform solves this by enabling organizations to create AI Data Scientists tailored to their specific business context and needs. Teams can collaborate in a multi-agent environment, ensuring human oversight across the entire workflow and making AI-powered data science trustworthy and accessible to everyone – from analysts to business leaders.

Seamlessly create and share customized data science agents within a secure environment that protects sensitive information, enabling true enterprise-wide collaboration. A

We power industry leaders, including Cisco, Johnson & Johnson, Canon, and McCann Worldgroup, to accelerate and scale their data science capability.

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