Neel Somani is a quant engineer turned content creator covering power markets, AI infrastructure, and crypto. In this episode of The Hedgineer Podcast, we dig into how the AI boom is reshaping energy markets, how rising compute costs are forcing companies to measure AI ROI, and whether open source models are changing the build vs. buy decision.

About the Guest

Neel Somani is a technologist and researcher focused on the intersection of machine learning, commodities, and formal methods. Formerly a quantitative developer in the power and commodities space, he has recently gained prominence for his work in mechanistic interpretability and his contributions to solving Erdős problems using large language models.

Follow Neel on X at @neelsomani, TikTok at @neelsalami, and Instagram at @neelsalami

About Hedgineer

Hedgineer is building the AI platform for institutional investing — deploying agents, skills, and data connectors directly inside hedge funds and asset managers to transform investment and operational workflows.

The Hedgineer Podcast follows CEO Michael Watson and COO Jhanvi Virani as they navigate the frontier of AI adoption in finance, sharing unfiltered perspectives from the teams, guests, and problems they work with every day.

Subscribe for weekly analysis on AI infrastructure and institutional finance.

Watch the full episode on Spotify or YouTube at youtube.com/@hedgineer.

Listen wherever you get your podcasts.

Connect with us on LinkedIn at linkedin.com/company/hedgineer-io or reach out at podcast@hedgineer.io.

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SaaS companies are pivoting: less investment in the dashboard, more in the API. Salesforce's headless MCP suite, Ramp's CLI, Linear's AI connectors — the pattern is the same. Products are being rebuilt for agents, not humans.

In this episode, Jhanvi and Michael dig into what's driving the shift and what it means for funds evaluating their stack. They also get into the architecture question that's coming up with every data vendor they talk to: how do you actually design a good MCP server? They break down the difference between open-source and closed-source skills, where intelligence belongs in the stack, and why the firms that win this next wave won't look like tech companies in the traditional sense.

About Our Hosts:

Michael Watson is the co-host of The Hedgineer Podcast, CEO of Hedgineer, and a technologist focused on deploying AI within the institutional investment space.

Jhanvi Virani is the COO of Hedgineer and co-host, specializing in scaling operations and technology platforms for hedge funds.

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Available wherever you get your podcasts!

Video available on YouTube and Spotify

youtube.com/@hedgineer

Questions? Topics you’d like for us to discuss? Email us at podcast@hedgineer.io

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#AIEngineering #InstitutionalInvesting #AssetManagement

The Season 2 finale of The Hedgineer Podcast features the return of Thomas Li, Co-founder and CEO of Daloopa, for his third appearance on the show. This episode marks a significant milestone as we transition into a new chapter for the podcast.

Before diving into the discussion, host Michael Watson announces a major shift for the upcoming season. Starting next week, The Hedgineer Podcast will move to a weekly release schedule to provide more frequent insights into the rapidly evolving world of technology, data, and AI. Joining the show as a permanent co-host is Jhanvi Virani, Hedgineer’s COO, who will help anchor our weekly updates and industry analysis.

In this finale, Michael and Thomas explore the decision to open-source Daloopa’s "investor library" of skills and agents—a move that challenges the historically closed-off nature of the financial data ecosystem. They discuss the philosophy behind treating AI agents as "text files" that can be refined by a community of sophisticated investors, effectively turning what was once proprietary alpha into the new industry beta.

The conversation delves into the technical obsession required to serve institutional clients, particularly regarding latency. Thomas explains why Daloopa prioritizes parsing unstructured press wires over waiting for structured SEC filings: in high-stakes markets, saving a few minutes of "server lag" is the difference between a successful trade and a missed opportunity.

We also cover the strategic landscape of building on frontier models. Thomas shares his experience partnering with Anthropic to build their Excel plugin and discusses whether evolving LLMs are a "wind behind the sail" or an existential risk for specialized fintech companies.

• The Open-Source Investor Library: Why Daloopa is providing its corpus of fundamental investing skills to the community and how 100+ hedge funds are already contributing back.
• Latency as a Moat: The engineering challenge of bypassing SEC server lag by parsing raw press wires to deliver verified data in seconds.
• Agents vs. Chat: Why the future of finance lies in agentic workflows (like "Scout" and "Claude Code") rather than simple prompt-and-response interfaces.
• Internal AI Adoption: How Daloopa uses AI internally—from analyzing customer feedback to helping sales teams prep for meetings—without hiring "AI Engineers," but by making everyone an AI user.

• 00:00 – Season 3 Announcement: Weekly episodes and new co-host Jhanvi Virani
• 04:15 – The decision to open-source the investor library of skills
• 11:30 – Why an "Agent" is just a text file and the power of community iteration
• 18:45 – Monetizing the "Engine": Ferrari’s philosophy applied to financial data
• 26:20 – The transition from Alpha to Beta in AI-driven research
• 35:10 – Partnering with Anthropic and the future of Excel-based agents
• 42:00 – Obsessing over seconds: Parsing press wires vs. SEC filings

About the Guest: Thomas Li is the Co-founder and CEO of Daloopa, a provider of high-fidelity data for company financials and KPIs.

About the Host: Michael Watson is the founder of Hedgineer, building data and AI platforms for institutional asset managers.

Subscribe for weekly analysis starting next season.

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