Without creativity, technology optimizes what already exists. Without engineering, ideas never become real. Exponential happens where imagination meets execution.
This is where artists meet builders. Where investors meet engineers. Where markets meet machines. Real conversations. Real systems. Real impact.
Creativity feeds AI. Engineering makes it real. Together, they shape what comes next.
Welcome to Exponential.
Leaders from top financial & tech institutions
Real work, real lessons, real impact.
Ideas you won't hear at mainstream conferences.
Invitation-only for leaders & builders
Exponential London 2026
Every era of finance has been defined by an information advantage: the ticker tape, the Bloomberg terminal, the quant. The next one will be defined by agents: software that researches, reasons, and acts on behalf of analysts, PMs, and treasurers at machine speed. But agents are only as good as the ground truth they stand on. In this keynote, Armando lays out a blueprint for the agent-native financial firm, how leading institutions are rewiring research, risk, and decision-making around AI infrastructure, what separates the firms compounding from those still piloting, and why the exponential gap between AI leaders and laggards is about to become uncrossable.
Drawing on both research and real-world practice, this talk explores how data becomes financially relevant across modern quantitative workflows.
The edge is no longer in having more data, but in understanding how narratives emerge, spread across sources, and eventually influence markets. In a world of commoditized models, advantage belongs to those who know not just what data says, but when it starts to matter.
We bring together leaders from across both the buy side and sell side to explore how AI is reshaping the foundations of modern finance, from research production and information flows to investment workflows and decision-making. The discussion will focus on what is actually working inside financial institutions today, where the operational challenges remain, and how firms are moving from isolated AI experiments toward real production-grade systems.
This panel brings together leaders building the infrastructure layer powering the next generation of financial AI. Spanning cloud computing, data platforms, and AI-native search and retrieval systems, the discussion will explore what it takes to operationalize AI at scale inside financial institutions — from data architecture and model deployment to real-time retrieval, performance, and governance. The focus is not on AI demos, but on the systems and infrastructure required to make AI reliable, scalable, and production-ready for finance.
Aakarsh will explore the evolution of the Bigdata.com platform in a world increasingly defined by workflows, agents, and LLM connectors. As AI shifts from standalone applications to deeply integrated systems, the session will examine how financial institutions are rethinking the infrastructure layer connecting data, models, and decision-making.
The discussion will cover the rise of AI-native workflows, the growing importance of interoperability across platforms, and why the future of financial AI will depend less on isolated models and more on connected, domain-specific intelligence systems.
Financial analysts spend hours stitching together filings, news, and market data before the real thinking begins. In this session, we'll show how the Bigdata connector turns Claude into a research partner that can pull company tearsheets, surface sentiment shifts, scan earnings events, and build comparable sets — all from a single conversation.
We will listen to the leaders shaping the future of financial content, research distribution, and AI-ready data ecosystems. As AI becomes embedded into investment workflows, the value of trusted, structured, and machine-readable content has never been more important. The discussion will explore how financial information is being transformed, enriched, and delivered for the next generation of AI-powered research and decision-making systems.
NLP-driven alpha is no longer the central debate. The more interesting question is where teams should actually differentiate.
For over a decade, structured analytics has been the primary layer of competition. But with LLMs and search-native infrastructure, the frontier is shifting from consuming pre-computed structure to generating new structure dynamically, scoped to a specific investment thesis.
In this keynote, Peter explores the workflow that makes universe-scale dataset creation economically viable, from retrieval and validation to thematic signal construction, and presents two thematic backtests built on top of it.
Welcoming experienced investors and market practitioners to discuss how AI and alternative data are reshaping the future of investing. The conversation will explore where AI is already creating a measurable edge across research, signal generation, and portfolio construction — and where the industry still struggles to separate noise from real value. With models increasingly commoditized, the focus shifts toward data quality, workflow integration, and the ability to turn information into actionable investment insight.
Financial markets have always run on information, but the nature of that information, and how it flows, is changing at an unprecedented pace. AI is collapsing the distance between raw data and actionable insight, creating both extraordinary opportunity and new forms of risk. In this keynote, Adriana examines the strategic implications of a world where AI increasingly mediates the relationship between information and decision-making, and where trust, provenance, and interpretability become defining competitive advantages. A session for leaders thinking beyond adoption, toward architecture.
This panel brings together leaders from across the financial information ecosystem to discuss how publishers and content providers are navigating the transition into the AI era. The conversation reflects an industry moving at different speeds, from organizations already deeply integrated into AI partnerships and workflows, to those still defining their long-term strategy.
The discussion will explore how media organizations protect the journalistic integrity, editorial standards, and trust their brands are built on while adapting to a world where AI increasingly becomes the interface between information and end users.
See yourself in the room?
"It was actually fascinating to see the convergence of everyone's view that seemed to generalize. Around a combination of both humans combined with AI to create value in the future."
"What I really enjoyed was the energy. There was a very strong positive energy of intellect in the crowd."
"From the moment I got into this venue, which was beautiful, to the opening act and just the whole design of it, I really take my hat off to RavenPack."
"The best part of the event was, in my opinion, seeing the RavenPack team in person. And it was great to have also my team come here and get to meet everyone in person and just, there's so much AI, the personal component is forgotten and that's really nice."
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