Proven Wins, On Data You Already Own.

Not One Big Bet

This isn't a single leap into AI. It's a set of proven, reinforcing wins, each one already working at real firms, and each within reach of a firm your size now. They compound: your meetings build a firm memory, that memory sharpens your coaching, your tracked data aims your marketing, and the whole system gets smarter every quarter on data you own. Start with one. Each win funds the next.

We'll walk through a few of the biggest here. There are more proven plays we can point to when you're ready.

Four Wins, One Foundation

Everything here grows from one foundation, and keeps growing. Coaching from your best, found money, advisor retention, sharper marketing: one engine, your conversations and your data, made usable. Start with one piece. Each piece makes the next one stronger, and the firm you're building gets more valuable the whole way.

Give Every Advisor Their Week Back

Advisors lose more than an hour of prep and follow-up for every hour in a client meeting, then re-key all of it into the CRM. AI meeting intelligence listens, then drafts the summary, the follow-up, and the CRM entry for the advisor to approve.

The first move: point a leading assistant at meetings you already record, 3 to 4 advisors who opt in, and agree what "working" means before anyone commits.

They Tested Before They Trusted

Focus Financial

An 800-advisor network ran the two leading meeting tools head-to-head for eight weeks with 40 advisors, then rolled out the winner. Advisors reported ~70% of meeting prep, notes, and follow-up time gone.

Internal survey reported in industry press; winning tool is the current category leader by adoption.

Focus Financial: How They Actually Did It

• The setupFocus Financial Partners, a ~$500B RIA aggregator, needed to choose an AI meeting tool across its firms. They didn't trust a sales demo.
• The testAn 8-week pilot. 40 advisors. The tool (Jump) run head-to-head against another vendor, in real client meetings, judged on criteria set before the pilot began. The firm later said Jump ranked #1 among more than 40 AI pilots they ran that year.
• The resultAn internal survey found Jump cut time on meeting prep, note-taking, documentation, and follow-up by ~70%, plus a reported "meaningful increase in overall organic growth rate." Rollout to 800 advisors followed.
• The takeaway for usThis is the exact method we'd run at your scale: pilot, measure against pre-set bars, then commit. We're borrowing a proven playbook, not improvising.

InvestmentNews & Business Wire (2026). The 70% is an internal survey, credible but self-reported; the independent floor remains 4 to 6 hrs/advisor/week.

A Firm Like Yours

Korhorn Financial

A small Indiana advisory firm adopted an AI meeting assistant: ~80% of post-meeting admin gone, roughly a full workday back per advisor each week, redirected into dozens of new client relationships a year.

Vendor case study (named firm). The independently measured floor across a large network pilot is 4 to 6 hours/advisor/week, the number we'd plan on.

Korhorn: How They Actually Did It

• The setupA small Indiana advisory firm whose advisors were drowning in post-meeting admin, which capped how many new households they could take on.
• The howThey deployed an AI meeting assistant (Zocks) and wired it into their CRM and planning software. The key move: instead of just transcribing, the tool extracted structured data from conversations and auto-filled planning forms and CRM fields directly.
• The result~80% reduction in post-meeting admin, 8+ hours/advisor/week freed, and critically, that capacity translated into roughly 36 new client relationships per advisor per year, without burnout.
• The takeaway for usThe win wasn't transcription, it was turning unstructured conversation into structured inputs mapped to their own systems. And it worked on their existing CRM and planning tools, not a single prescribed stack, so the approach isn't locked to whatever you use.

Vendor case study (Zocks). Numbers are vendor-reported; plan on the independent 4 to 6 hr floor and treat 8 hrs / 36 clients as the optimistic ceiling.

Aim the Marketing You Already Pay For

You spend real money on seminars, radio, mailers, and social, but can't yet say which channels actually produce clients, and follow-up gets spread evenly across leads that were never going to convert. AI scoring ranks who's most likely to become a client, so your best prospects get the fastest, most personal attention.

The first move: build the ideal-client picture from your own multi-year conversion outcomes, then score new leads against it. That's stronger fuel than any vendor's generic signals.

Same Spend, Better Aim

Amplius Wealth + Catchlight

A growing firm let AI score and rank its existing leads so advisors gave the best prospects the fastest attention. Reported lead-to-client conversion roughly tripled, no new marketing dollars.

Vendor-adjacent reporting. Your version is stronger: build the ideal-client picture from your own multi-year conversion outcomes, not a vendor's generic signals.

Amplius + Catchlight: How They Actually Did It

• The setupAmplius Wealth Advisors (~$941M AUM, Dynasty network). The problem: limited advisor hours spread evenly across leads of wildly different quality.
• The howThey ran leads through Catchlight, a lead-scoring tool that scores each prospect against up to ~2,000 data points, benchmarked against 170,000+ prior conversions, sorting by likelihood to convert and likely value. Advisors gave the top-ranked prospects the fastest, most personal follow-up.
• The resultLead-to-client conversion moved from ~1 to 2% up to 3 to 6%, roughly a tripling, on the same lead spend.
• The honest caveat, and why it helps youAmplius's own exec admits Catchlight wasn't fully integrated with his CRM and required manual screening. That candor is the point: this is a realistic workflow, not a frictionless miracle. And your version is stronger, because you'd score against your own multi-year conversion outcomes rather than a vendor's generic model.

WealthManagement.com, named-advisor account. Independent. Catchlight ~$150/seat/mo.

≈ $17.6M

sitting in relationships you already have

Held-away assets: the old 401(k), the inherited account, the brokerage elsewhere, mentioned in meetings, never captured.

Illustrative, deliberately conservative: a client base your size, roughly 1 in 10 with about $200K held away. The real number is in your transcripts, and finding it is the project.

Find the Money Already in the Room

Clients mention old 401(k)s, inherited accounts, and brokerage held elsewhere in meetings all the time, and that signal sits buried in the transcript pile. Mining the conversation corpus surfaces it, ranked by estimated size, as a task queue for advisors.

The natural two stages: identify and rank the opportunities now, decide execution later with counsel. The money is already inside relationships you have.

Capture the Craft, Keep the Knowledge

Your top advisors carry a craft most couldn't put into words: how they open, how they handle the hard question, when to push and when to listen. And when an advisor leaves, that knowledge walks out the door. Mining every meeting captures the craft and turns your transcripts into a searchable firm memory, so top-performer patterns become coaching for everyone, and the firm can always answer what was promised.

The first move: structure and mine the meetings you record, so the memory is there before you need it.

Real Value to Your Advisors

Give your advisors a day that works for them. A system that prepares them, hands them opportunities, adds structure to their day, and delivers results: better conversations, happier clients, better outcomes all around. And once a quarter, one page that makes the firm's value impossible to miss: leads delivered, assets sourced, hours returned.

Turn a Daily Grind Into an Advantage

Compliance is non-negotiable, and today it's a manual daily effort. The same conversation corpus that powers everything above can make it easier and stronger: automated checks that validate recommendations against the rules, natural-language summaries generated for you, and more of your client conversations captured into the record automatically. A rigorous, well-documented compliance posture isn't only safety, it's something you can show clients and buyers.

The first move: capture more of the record automatically, then layer the checks on top.

One Quick Win to Start

The Daily Data Chore

The daily back-and-forth between your custodian and your compliance system is exactly the kind of friction worth removing first. From what we can see, this isn't a missing capability. Both systems already support an automated data feed that was most likely never switched on. The likely fix is configuration, not custom software, so it's something we could stand up together fairly quickly: days to weeks, not months. We'd confirm the exact path first, but it's a strong early candidate for a fast, visible win.

You're Not Behind, You're Ahead on Data

Everybody feels behind. And yet: 63% of firms "use AI," but only 1 in 10 has it working for the business. Most "adoption" is drafting emails. The integrated tenth needs two things: proprietary data and operating discipline. You have both, which means you're not behind on adoption, you're ahead on data and behind only on activation.

Independent 2026 study, 533 advisory firms.

The Advisor's Role

AI doesn't shrink the advisor's role. It shrinks everything around it. Fewer than 1 in 5 clients would trust AI alone with their money. What they're buying is human: steady judgment when markets get scary, and someone who knows them.

Independent 2025 consumer research, happy to share specifics.

The Lens Is Yours to Hold

The data is yours. So is the judgment the data can't supply. AI can surface a pattern. Only you know if it fits this client, this town, this market: the things you've learned that were never written down. And control matters: when you lean on other people's interpretations of your data, you don't fully own it. The real value is keeping the data, how it's processed, and the foundation it sits on in your hands, with AI doing the fetching, never the deciding.

No One Can Start From Zero Every Day

By default, AI forgets everything overnight. For a person, that's a nuisance. For a firm, it's the line that's forming: between those whose tools remember the business and those starting over each morning. Every meeting, every lead, every lesson, compounding in a foundation you own.

The edge: the firms that own their data and put it to work, rather than lean on someone else's version of it, are the ones AI turns into a real, lasting advantage.

First, Build the Foundation

Before any of this compounds, the basics have to be in place, and most firms skip them. Decide which AI tools you standardize on. Capture and carry context between conversations instead of losing it in scattered chats. Set honest expectations: these are probabilistic systems, so we design for that rather than trusting perfect recall. And give your team one shared way to work, kept current, with a little practice. This is what turns AI from scattered experiments into a system you control, where the value is yours and not locked inside someone else's interpretation of your data.

Put Your Own Content to Work

With the foundation in place, the highest-value early move is mining what you already own. Set up a way to transcribe and analyze your meetings, calls, and videos, processed on your terms, even locally. Then add a layer of logic on top that pulls out the substance: opportunities, commitments, the craft of your best people. That layered structure on your own data is where the durable value lives, and it's the groundwork every payoff in this deck is built on.

Next Steps

A careful first step, and the groundwork underneath it. Point a leading meeting assistant at meetings you already record: 3 to 4 advisors who opt in. It writes summaries and follow-ups and files notes automatically, and we agree what "working" means before anyone commits. In parallel, two quick, concrete moves: stand up the custodian-to-compliance feed, and confirm the right setup to transcribe your library efficiently, the groundwork for everything above.

The Foundation Under These Recommendations

1. 01Five independent deep-research passes, run across four of the most capable AI systems available and cross-examined against one another, reconciled into a single evidence base of more than 250 sources: industry data, regulatory guidance, vendor documentation, named real-world case studies, and the firm's own operational context.
2. 02Every finding was traced to its origin and labeled by how far it could be trusted: independently verified, vendor-claimed, or illustrative.
3. 03AI was used not as a shortcut but as an instrument: to widen the search, pressure-test every conclusion, and hold the whole effort to a standard of calibration over optimism.
4. 04What remains isn't opinion about what might work, but a tiered, source-grounded view of exactly where the real, defensible opportunities lie.

What Connects to the Foundation

How Deep This Went

Calibration over optimism: marketing spin separated from substantiated fact.