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AI Business & IndustryFortune AIPublished: Aug 21, 2026, 19:03 JST2 min read

Marloo hits 37% monthly growth helping financial advisers scale

Marloo hits 37% monthly growth helping financial advisers scale

Key takeaway

  • Marloo, an AI startup helping financial advisers manage growing portfolio complexity, has onboarded over 900 advisory firms across eight countries in 15 months.

  • The company is growing 37% monthly and expanding into the U.S. AI augments adviser time but cannot replace human judgment on client priorities.

3 Key Points

  1. What happened

    Marloo, an AI startup founded by the creators of retail investment platforms Sharesies and Lightyear (which manage more than £7 billion in assets), has onboarded more than 900 paying advisory firms across eight countries in 15 months and is expanding into the U.S. The company has raised $13 million ($3 million pre-seed, $10 million seed, six months apart) and is averaging 37% monthly revenue growth since inception.

  2. Why it matters

    Financial advisers face a time crunch as investment options have expanded—institutional asset classes once limited to the wealthy are now accessible to ordinary investors at lower minimums, forcing advisers to spend more time personalizing portfolios rather than fitting clients into standard models. Marloo's AI tools help advisers work through complex client circumstances faster (narrowing down which clients an interest rate move affects, modeling individual portfolios without manual rebuilding), freeing them to focus on the human judgment that decides which goals matter and what compromises clients can accept.

  3. What to watch

    The founders entered the hardest, most regulated markets first; a new market now takes days rather than months, according to the founders. The company is expanding into the U.S. after proving the model across eight countries.

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Context & Analysis

Marloo's rapid scaling reflects a structural shift in financial advice. For decades, advisers managed portfolios by dividing assets into fixed categories—stocks, bonds, property, alternatives—and fitting clients into standard models. But the landscape has changed: institutional-only assets are now packaged for retail investors at much lower minimums (from millions down to thousands), expanding both the range of investment options and the diversity of client circumstances. A parent saving for school fees needs a different portfolio strategy than an entrepreneur preparing to sell a company, even if they have similar wealth and risk appetite. This means advisers must ask more practical, personalized questions about liquidity, income needs, crisis resilience, and time horizon—questions that take significantly more time per client than fitting them into a template.

The founders' earlier companies, Sharesies and Lightyear, illustrated this frustration firsthand: they managed over £7 billion in assets but could offer only generic reassurance during volatility because they could not provide personalized advice. Marloo's core insight is that AI cannot replace the human judgment required to prioritize conflicting client goals, but it can reclaim the time advisers lose to administrative work and manual portfolio modeling. By entering the hardest, most regulated markets first (and condensing market entry from months to days), Marloo has proven the model is portable across jurisdictions, positioning it to scale as advisers across geographies face the same complexity squeeze.

FAQ

How many advisory firms is Marloo working with?
Marloo has onboarded more than 900 paying advisory firms across eight countries.
How much funding has Marloo raised?
The company has raised $13 million total: $3 million in a pre-seed round and $10 million in a seed round, with the two rounds only six months apart.
What does Marloo's AI actually do for financial advisers?
The AI helps advisers model individual client circumstances without spending hours rebuilding portfolios manually and can narrow down which clients are most affected by market moves, letting advisers focus on the human judgment needed to understand client goals and acceptable trade-offs.

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