AI for Advisors

Mark Heynen, James Cantwell

Exploring the intersection of AI & money.

  1. Aug 20

    What Comes After the AI Note-Taker: Aaron Klein @ Contio, Tom Fields @ Fynancial

    AI note-takers promised to fix advisor meetings. Adoption is nearly universal — and yet client retention hasn't meaningfully improved, and most advisors still walk into reviews without a real game plan. So what did the industry actually solve? Aaron Klein, who spent 12 years building Riskalyze into a category before starting over, argues the note-taker wave started at the wrong end of the problem: capturing conversations is easy, turning them into decisions and follow-through is the actual job. His new company, Contio, is built as an operating system layer rather than a standalone app — meant for partners to build on top of, not to lock advisors into. That's exactly what Tom Fields did. As the first partner built on Contio's MeetingOS, his company Fynancial takes that meeting data and turns it into the always-on mobile experience advisors' clients already expect from every other app on their phone. Together, they make the case that the real unlock isn't smarter transcription — it's open data, faster meeting prep, and giving clients a channel that isn't buried in email. What You'll Learn: Why Aaron Klein calls AI note-taking "starting at the wrong end of the problem"The difference between an "operating system" and a "platform" — and why Contio deliberately chose OSHow Tom Fields built Fynancial as the first partner on Contio's MeetingOS, and what that partnership actually does for advisorsWhy locking up client data is a losing long-term strategy, even if it's tempting short-termWhy older clients default to their phone as their primary computer — and what that means for advisor tech decisionsWhy meeting prep should happen a week or two out, not 30 minutes beforeThe rapid-fire debate on the most overrated and underrated AI technology in wealth management right nowKey Takeaways: AI note-takers solved the wrong problem.→ Recording a meeting was never the bottleneck — turning what gets said into what gets done was. An operating system beats a platform.→ Contio isn't trying to maximize time in its own app. It's built so partners like Fynancial can build entire products on top of its data layer. Locking up data is a losing strategy.→ Firms that don't expose clear APIs or MCP access will lose customers to those that do — full stop. Speed is a relationship advantage, not just an efficiency one.→ In a trust-driven business, how fast you respond to a client is itself part of the service. Meeting prep should happen days before the meeting, not minutes before.→ The easier prep gets, the more tempting it is to do it last-minute — which defeats the point. Why This Episode Matters:The AI note-taker wave made it easy to believe the meeting problem was already solved. This episode makes the opposite case: recording a meeting was always the easy part. The advisors and platforms that win from here will be the ones that treat meeting data as fuel for faster decisions and open ecosystems — not another walled garden. Aaron Klein and Tom Fields are building from opposite ends of that same idea, and the partnership between their companies is a live example of what an open, decision-first approach to meeting AI can look like in practice.

  2. Aug 13

    Why AI Adoption Fails: Vineet Mohan @ FastTrackr AI, Frantz Widmaier @ Altitude CRM

    Every advisor who's changed firms knows the drill: a blank intake form, a client asked to re-explain a hundred data points they've already given someone else, and a 90-day scramble that leaks 10-20% of assets out the door along the way. The tools to fix this have existed for a while. What's actually been missing is someone willing to own the entire mess — not just the data pipes, but the paperwork, the tracking, and the hundred spreadsheets nobody can find. This week, Mark and James talk to two founders tackling that exact problem from opposite directions. Vineet Mohan spent 14 years at HSBC before building FastTrackr AI, which handles advisor transitions end-to-end rather than just connecting data sources. Frantz Widmaier inherited a 45-year-old consulting firm, Bill Good Marketing, and is turning it into Altitude, an AI-native CRM built around an assistant called Pathfinder. The conversation keeps circling back to the same tension: the technology to move faster is already here. What's slow is getting advisors — and their clients — to trust it. What You'll Learn: - Why advisor transitions still take up to 90 days and why that delay costs firms real assets - The three distinct reasons advisors change firms — demographics, M&A, and breakaways — and why the "unlock" AI offers differs for each - Why "plug and play" is a myth for multi-step, edge-case-heavy workflows, even if it works fine for something like meeting assistants - What happened when Altitude's users pushed back against a better, but different, CRM interface - Why building AI features fast can outpace your users' ability to accept the change - How Salesforce going headless and MCP-friendly changes the build-vs-integrate calculus for CRM startups - Why the "harness layer" — the logic sitting between the model and the system of record — may be the more durable asset than either the model or the CRM - How advisor and client attitudes toward AI security are shifting Key Takeaways: Adoption fails on change management, not capability. → The tools already exist. The bottleneck is trust. Advisor transitions leak real money, not just time. → 10-20% of assets fall away during a firm change due to a slow, impersonal process. Plug and play works for narrow tasks, not messy workflows. → A meeting assistant can be plug and play; a multi-step transition still needs a human in the loop. Speed of building doesn't equal speed of adoption. → Shipping fast can backfire without walking users through the change in phases. The application layer is becoming the durable asset. → As models and CRMs commoditize, the "harness layer" between them may hold the real advantage. Why This Episode Matters: Most AI-in-wealth-management conversations focus on what the technology can now do. This one is more useful because it focuses on what still gets in the way after: users resisting a redesigned CRM, clients quietly more comfortable with AI than advisors assume, and a transition process that's slow less because of missing data than a poor experience. The practical takeaway for advisors: ask less about what a tool can do, and more about how a vendor plans to walk your team and clients through the change.

  3. Aug 6

    Will AI Replace the CRM?: Thomas Clawson @ Slant

    Most firms think AI changes software. The bigger shift is that AI changes workflows. As AI becomes the primary interface for getting work done, it's forcing firms to rethink a fundamental question: does the CRM still matter—or is it becoming obsolete? In this episode of AI for Advisors, James Cantwell and Mark Heynen sit down with Thomas Clawson, Co-Founder of Slant, to explore why AI-native software looks fundamentally different from legacy CRM platforms, what advisors actually need from a system of record, and why the future may be less about adding more technology and more about making existing workflows disappear. Why AI-native CRM isn't just legacy software with a chatbot attached Whether AI agents will replace CRMs—or make them even more important Why advisors still need a trusted system of record How AI is changing client expectations before they ever meet an advisor The tradeoffs between building specialized tools versus all-in-one platforms Why customer experience has become a competitive advantage for advisor technology How Slant went from marketing automation to one of wealth management's fastest-growing AI-native CRMs The CRM isn't disappearing → AI changes how advisors interact with software, but firms still need a trusted source of truth. AI shifts the focus from software to workflows → The goal isn't more tools—it's fewer manual processes. Great advisor technology reduces operational complexity → The best platforms eliminate spreadsheets, disconnected apps, and repetitive work. Clients are arriving more informed than ever → AI isn't replacing advisors—it changes the conversations clients expect to have. Relationships remain the competitive advantage → AI can automate tasks, but trust is still built between people. The real question isn't whether AI replaces the CRM. It's whether today's CRM is designed for the way advisors will work tomorrow. As AI takes over more operational work, the firms that succeed won't necessarily have the biggest technology stack. They'll have systems that connect information, automate routine tasks, and help advisors spend more time where they create the most value: with clients. That's the conversation this episode explores.

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Exploring the intersection of AI & money.

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