Nemo.money’s Nicholas Scott on AI-guided investing, truthful data, and where regulation really leads
On this SlateCast episode, Nemo.money CEO Nicholas Scott joined CryptoSlate’s Liam “Akiba” Wright and Nate Whitehill to discuss AI-guided investing grounded in verified data. Scott outlined Nemo’s portfolio-insight engine, privacy safeguards, and thematic discovery features, while contrasting progressive UAE regulations with slower UK oversight and highlighting stablecoins’ promise for frictionless settlements. The conversation underscored guidance over advice and the future of personalized, compliant fintech innovation.
From slideware to a live, award-winning product
Nemo.money began life in 2021 in a crowded field of investing apps. Scott explained that the team quickly had to choose which core user problem to solve. Rather than building primarily for education, Nemo focused on surfacing actionable opportunities aligned to a user’s goals and risk appetite—helping people decide what to buy and when, without recommending a single security to any individual.
“We don’t have permission to give … advice,” Scott noted, emphasizing that Nemo presents options and context while leaving decisions to the user.
Guidance, not advice: how Nemo frames AI
A centerpiece is Nemo’s daily, AI-driven “portfolio insight.” With a tap, users receive a concise brief on what moved in their holdings over the last 24 hours—stitched together from relevant headlines and price action—plus ideas to improve diversification. The experience is designed to save time and surface “interesting stories,” not just the biggest movers, so users learn why their portfolio behaved the way it did and explore adjacent assets or ETFs that might rebalance risk.
Wright underscored the point that any AI summary must be grounded:
“And it’s amazing writing that back, but it needs the fact to begin with. You cannot get trust.”
Scott agreed, explaining Nemo’s strict separation between facts and language models: the team licenses fundamentals, volumes, and sentiment from tier‑one financial data vendors, then feeds that truth set into the LLM to generate user‑specific insights.
“We learned that early doors: buy from good data providers.”
Truth first: model strategy and privacy
Not every feature demands the latest, priciest model. For factual, template‑like updates (e.g., refreshed company health summaries generated from fundamentals), Nemo can rely on established models. For problem‑solving tasks—like suggesting diversification paths from a user’s current holdings—the company opts for newer models. Scott also stressed privacy: user portfolios are anonymized before being processed, and personally identifiable information isn’t passed to external AI tools.
Where regulation really leads: UAE vs. UK (and stablecoins)
Asked where the most forward‑thinking regulation is emerging for AI and crypto, Scott pointed to the UAE. Dubai’s willingness to pilot and fund innovation allows companies like Nemo to iterate faster, he said, contrasting that pace with the UK’s slower regulatory cadence. Stablecoins also featured: clearer frameworks promise to simplify the cross‑border payments that brokers wrestle with daily—an area where crypto’s original “value transfer” design can meaningfully reduce friction.
Beyond mega‑caps: discovery at the edges
Nemo lists thousands of instruments across asset classes, with crypto currently available via CFDs as the company explores deeper integrations. A key KPI for the team is breadth of engagement: users aren’t just piling into the same handful of names. Features that cluster securities around investment ideas (“AI infrastructure,” “carbon capture,” etc.) encourage discovery aligned with each user’s interests and objectives rather than simply amplifying the biggest tech stocks.
Wright captured a common research pain point—finding the less obvious picks around a theme (e.g., suppliers to chip manufacturers). Nemo’s forthcoming capability auto‑assembles thematic baskets on the fly from a user’s natural‑language query and explains the relevant sub‑sectors in plain English.
Personalization: from briefings to AI‑generated podcasts
The next step in Nemo’s portfolio brief is format flexibility. Scott revealed the team is piloting an AI‑generated audio version—essentially a personalized “mini‑podcast” that can inject timely context (upcoming macro events like FOMC, non‑farm payrolls, or crypto‑specific catalysts) and adapt depth or tone to the listener’s sophistication. The long‑term vision is content that meets users where they are—channel, language, and complexity—without condescension or data leakage.
Wright also pressed on availability. Nemo launched under Abu Dhabi regulation and is seeing traction across the Middle East and Africa with organic interest from Europe. The U.S. market remains on the roadmap, with the team watching regulatory movement closely.
Wright, on CFDs: “It’s a trade, not an investment, isn’t it?” — a reminder that product design and disclosures must match user intent and jurisdictional rules.
Closing
The SlateCast episode with Nicholas Scott offered a clear view of where AI‑guided investing is headed: truthful data first, models second; guidance over advice; and personalization without compromising privacy. From discovery tools that go beyond mega‑caps to AI‑generated portfolio briefings, Nemo’s approach shows how careful product choices can turn noise into signal.
As regulatory frameworks around AI and stablecoins mature—and more jurisdictions pilot pragmatic rules—the fusion of digital assets and traditional markets will only accelerate. The intersection of compliant innovation, user‑centric design, and trustworthy data is set to be one of the most consequential areas to watch in the coming years.