Nitrogen Launches Its Own AI Notetaker (And More Of The Latest In Financial #AdvisorTech – August 2025)

Nitrogen Launches "AI Meeting Center", Continuing The Shift Towards Embedded AI Notetakers Over Standalone Tools

Over the last two years there has been a raft of new AI-powered meeting note tools, capitalizing on the improvements in Large Language Model (LLM) technology to develop tools that can convert the transcribed text of a meeting into a summary of key points, suggestions for follow-up tasks, and a post-meeting client email, while also often pushing data to the advisor's CRM and financial planning or other software. All of which can serve to greatly expedite the process of preparing for and following up after client meetings, which Kitces Research on Advisor Productivity has found takes an average of one hour each (or two hours total) per meeting without the use of an AI notetaker.

At first, nearly all of the new AI notetakers existed as standalone products, either as general-purpose tools like Fathom, Fireflies, or Zoom's AI Companion, or as financial advisor-specific solutions like Jump, Zocks, Finmate AI, and numerous others that have arrived on the Kitces AdvisorTech Map in recent months. But although they're sold as standalone tools, they hardly stand alone within an advisor's tech stack: Since meeting-related tasks almost always involve other technology tools like the advisor's CRM (to archive meeting notes and kick off associated tasks), email (to compose and send the follow-up note to the client), and financial planning software (to update data based on information that comes out during the meeting), AI notetakers need to be used in conjunction with those tools as well. And indeed, a main selling point of early leaders in the category like Jump, Zocks, and Finmate was their ability to integrate with advisors' CRM systems (and increasingly with other systems like data gathering tools and financial planning software as well).

But the proliferation of standalone AI meeting note tools that (despite some differences around ancillary features like template customization and compliance controls) all perform essentially the same core function of AI notetaking while differentiating on the number and quality of their integrations raises a significant question: Why wouldn't existing tools such as CRMs simply embed AI notetakers within their own software, and eliminate the need for advisors to go back and forth between tools in order to use their AI meeting note software? Which has grave implications for the many standalone AI notetakers on the market, since once AI meeting notes are embedded in the software that advisors already use, there's little need to pay extra to a third party solution to provide it.

In this context, it's notable that Nitrogen has become the latest AdvisorTech provider to offer an embedded AI meeting note tool this month with the launch of its AI Meeting Center. Nitrogen's announcement is only the most recent in a growing wave of existing tools offering embedded AI notetakers, coming on the heels of Wealthbox building and releasing its own meeting note solution and Altruist acquiring the standalone tool Thyme.

This news further darkens the landscape for standalone AI meeting note tools. With a major CRM provider in Wealthbox, a major custodian in Altruist, and now a major proposal and sales enablement platform in Nitrogen all offering native AI notetakers bundled into the cost of their existing platforms, there are fewer and fewer advisors on the market who don't already have an AI meeting note tool available to them for no extra cost beyond what they're already paying for their software. And the Nitrogen news specifically is a blow to meeting note providers hoping to break into the broker-dealer space, since Nitrogen is already compliance approved and cybersecurity vetted most of the major broker-dealer platforms and would require significantly less due diligence to adopt than a standalone startup.

What's also becoming evident is that there's no clear agreement yet among technology providers about where AI meeting notes should 'live' in an advisor's tech stack. An advisor who uses Wealthbox for CRM, Altruist as a custodian, Nitrogen for proposal generation, and Zoom for virtual meetings now has no fewer than four different AI notetakers available to them, when there's no need or likely any desire for any advisor to use more than one at a time. Advisors can of course simply elect to use their favorite of the available options and ignore the others, but by and large technology users don't want to pay (in this case, bundled into the fee they pay for the rest of the software) for features that they don't plan to use. It would seem to make the most sense for AI notetaking to be embedded in the advisor's CRM given (1) the high adoption of CRM systems overall and (2) the significant overlap between meeting notes, tasks, and client communication; but the relative ease of building an AI meeting notes tool has so far led a wider range of providers to roll it out as a feature. Ultimately, time will tell as advisors vote with their feet on the different notetaker options available to them, and eventually the market will settle on what will eventually be the default for it to live.

The key point is that with a growing list of native AI notetakers in existing technology tools, the list of standalone solutions seems poised to shrink considerably. With the exception of early leaders like Jump and Zocks that have already managed to consolidate significant market share, it will get harder for the remaining tools to gain a foothold. For many tools, the remaining options may soon shrink down to either being acquired to be absorbed into an existing platform (as with Thyme's acquisition by Altruist) or alternatively to evolve in a new direction beyond meeting notes and into a less competitive field – perhaps by going deeper into agentic AI and performing actual tasks on the advisor's behalf rather than "just" summarizing meeting transcripts, or even by building their own CRM with embedded notetaking to compete more directly with solutions like Wealthbox. Either way, while we may see fewer new standalone AI notetakers going forward, it's apparent that the new wave of natively embedded AI meeting note solutions is just getting started.

New Research Finds That Integrations Are The Biggest Driver Of Satisfaction With Advisor Technology, But Have Little Impact On Productivity

One of the defining developments in advisor technology over the last 15 years has been the push to improve integration between different software tools. Once AdvisorTech tools fully transitioned to the cloud from desktop machines and servers in server closets, with the availability of APIs, it became possible for software solutions to "talk" to one another, and easier for new AdvisorTech vendors to launch. As advisors have relied more and more on increasing numbers of cloud-based technology tools, managing the need to enter and coordinate data across all of those tools became an increasing source of frustration – such that as of the 2023 Kitces Research Study on Advisor Technology, advisors on average were less satisfied with their technology stacks as a whole than they were with each of the individual components, stemming from their dissatisfaction with their technology tools' ability to efficiently and effectively work alongside one another. When technology tools' integration capabilities are quantified by integration score, a metric developed by technology consultant Ezra Group to measure the depth and quality of integration capabilities for AdvisorTech tools, the median provider as of this writing rates only 4.86 out of 10, showing that the AdvisorTech field as a whole has a long way to go when it comes to seamlessly integrating with each other.

In this light, it isn't surprising that, according to data in the upcoming 2025 Kitces Research on Advisor Technology (advance copy available at the Kitces Research Spotlight, with full report publicly available mid-September), the biggest driver of advisors' satisfaction with their tech stacks was the quality of integration between their different technology tools. In other words, advisors with less integrated tools were relatively unhappy with their technology lineup, while those with better integration capabilities were happier than average. Which makes sense, given how the level of integration between different tools can drastically affect how much advisors must tediously switch between multiple tools; entering the same data multiple times into different systems, and ensuring that all of the data is reflected consistently across each system, can be frustratingly time consuming, and so tech stacks that are interconnected enough to only require data to be entered once are naturally preferable to those without that level of connection.

The more surprising finding from the new technology study, however, is that while integration is the main driver of advisors' satisfaction with their tech stack, it has remarkably little relationship to advisor productivity metrics like revenue per advisor or even the firm's overall revenue per employee. Furthermore, neither advisors' overall satisfaction with their tech stack nor their own technological sophistication have any consistent relationship with advisor productivity: Although advisors with more integration tend to be more tech-savvy and happier with their tech stacks on average, they don't necessarily have more revenue on a per advisor or per team member basis than advisors who are less integrated, tech-savvy, or happy with their technology.

What does appear to drive advisor productivity, as found in previous research like the 2024 Kitces Research on Advisor Productivity, comes overwhelmingly down to two factors: the teams advisors have around them and the amount of staff support they receive, and how much revenue per client that the advisor earns (i.e., the affluence of the clientele themselves). Advisors with 1-2 support staff members directly on their team are consistently more productive than those with no support, since they can better leverage their time by delegating non-client-facing tasks. And advisors whose clients pay them more have more revenue per advisor and per employee than those whose clients pay less, and drive so much more revenue from their time that they achieve better productivity metrics even though they may work with fewer clients overall. However, neither of these factors appear to have any relation to the integration capabilities of the advisor's tech stack, the advisor's tech-savviness, or whether the advisor is even happy with their technology setup in the first place.

The takeaway from the latest research, then, is that any gains in productivity stemming from technology that seeks to make advisors more efficient are negligible compared to the productivity gains that can be made from the use of support staff and/or from serving higher value clients. Or in other words, advisors looking to earn more revenue would be better off either hiring staff to handle back- and middle-office tasks, or to move upmarket by offering higher value advisory services (and finding clients who will pay them commensurately higher), rather than chasing incremental efficiency gains by trying to optimize the technology they use. Which undermines the claim that's often made by software providers that the investment in the software will be easily made up for by the productivity gains that result from using it.

That said, there is some good news for technology providers in the Kitces Research findings. First, integration capabilities really do seem to matter when it comes to advisors' satisfaction with their technology, and so solutions that can help advisors to better integrate their tools with one another can result in more satisfied customers overall. Even if that satisfaction doesn't necessarily translate into greater productivity, it can still help drive an advisor's decision to choose one piece of software over another if they can have a better experience with the one that's more integrated.

The second positive is that there may truly be a compelling sales pitch for software that can actually assist advisors in the activities that do materially boost productivity For instance, tools that aid an advisor with going deeper into tax, estate, or business planning might help them attract more affluent (and higher paying) clients – not because they allow the advisor to work faster and churn through plans for a greater number of clients, but because they facilitate the advisor in doing better planning for the clients that they already have (or the clients that they don't have, but want to pursue). In fact, the recent Kitces AdvisorTech Research finds that advisors who focus on using technology for better client experiences and improved quality of advice are actually twice as productive as advisors who view the role of technology to be cost or time savings; in other words, advisors buying AdvisorTech for productivity purposes are less productive than those who use it to attract and retain higher-dollar clients.

The bottom line is that while features like integration capabilities that improve advisors' efficiency can make those advisors happier with their technology overall, they shouldn't necessarily be expected to have a significant financial ROI for the advisory firms that use them. Advisors may still decide that those tools are worth it purely for the reduced hassle and mental overhead that can come with more streamlined processes, and as firms get larger there is some level of tech-savviness they must implement or they will outright fall behind in firm efficiency and productivity; still, unless the technology actually facilitates the advisor with better leveraging their staff support or attracting higher paying clients, the technology's cost would best be considered a pure overhead expense rather than an investment that will see a meaningful financial return in margin improvement or staff savings. And for technology providers, the takeaway is that technology that can substantially improve advisors' quality of advice and client experience is more valuable in financial terms than tools that simply offer better efficiency – because as the research data shows, the sales pitch claim that more efficiency translates into better productivity doesn't seem to pan out in reality, while time after time the research shows that the advisors who really are growing their productivity are those who invest in better quality advice for the clients who can pay for it.

GReminders Launches "Do Anything" AI Agent, But Do Advisors Really Just Need Better Workflows?

Although financial advice itself varies drastically from client to client, the process of giving financial advice has proven capable of being highly systematized. At the core, there is the process of creating and implementing a financial plan, as exemplified by the 7-step financial planning process developed by CFP Board and taught to thousands of CFP candidates each year. And operationally, in the process of running an advisory firm there are numerous tasks that can be distilled into discrete and repeatable series of steps – from rebalancing client portfolios to opening accounts and moving money to client meeting preparation and follow-up. Which is why tools like workflows, checklists, and flowcharts can be so helpful for financial advisors: With so many actions, processes, and decisions that can be made systematically, a written or visual guide can clarify the path forward and the next best step to take.

Once a process is able to be systematized, it's often a natural next step for it to be automated via technology. And for most processes, the technology doesn't even need to be terribly sophisticated: Steps that are repeated the same way every time can be set up as a program that kicks off and repeats itself each time it's needed, while even more complex workflows that have different steps depending on various factors can be managed by a series of fairly simply algorithms (e.g., workflows with branching logic), as long as the decision-making criteria for each step remain constant.

In practice, however, few financial advisors seem to rely on technology to automate the processes used to run their practice. Not necessarily because the technology to do so doesn't exist – as mentioned, repeatable programs and algorithms to help automate workflows have existed for decades, and tools like Asana and Hubly have long been available for financial advisors to manage their workflows. Instead, the issue tends to be that many advisors never set down their processes into repeatable workflows to begin with – as evidenced by tools like Hubly that offer workflow support specifically for financial advisors struggling to gain traction as relatively few advisors implement workflows at all ( though notably, those who do seem to prefer having their CRM provide it instead of needing to pay for a standalone offering).

All of which makes it notable that GReminders, which provides meeting scheduling and management tools for financial advisors, has introduced what it describes as an AI-powered "Do Anything" assistant to automate advisor processes around client meetings. GReminders goes so far as to describe its new tool as a fully automated AI agent that autonomously completes pre- and post-meeting actions without prompting from the advisor, including generating pre-meeting preparation briefs and post-meeting follow-up emails, and logging meeting notes into the advisor's CRM system.

Although there's no fully agreed-upon definition of what an 'AI agent' really does, one reasonable definition would be a tool that can accomplish a task consisting of a series of steps that aren't defined in advance, but which the tool must figure out on its own (much like a human assistant might be asked to do a job without being explicitly told how to go about doing it). Except what GReminders' new tool appears to really do, despite the AI-heavy language, is to automate what was already a highly systematic set of before- and after-meeting workflows, which have already been greatly streamlined by the capabilities of AI meeting note tools like Jump and Zocks. In other words, there's no need for an AI agent to accomplish an advisor's before- and after-meeting tasks, because the steps in that process have already been defined and systematized to the point that they can be done by nothing more 'intelligent' than a simple algorithm captured by an established workflow in an existing software system.

Which is not to say that GReminders' assistant isn't useful. The ability to process and integrate data from different sources, stored in different formats, and present it in an easily digestible form truly is a valuable use case for AI. If GReminders really can search through calendar, email, and CRM systems and decide which information is worth highlighting in a pre-meeting brief, that might even represent a step towards what one could consider 'agentic' (though not all the way there, since it represents just one step in a defined process, where AI happens to be used to execute that step of the process by generating a multi-sourced pre-meeting brief). But if what's being promoted as a 'do-anything' assistant is in reality only capable of performing a handful of already highly systematized pre- and post-meeting processes, it seems like it's a long ways off from the promise of a truly autonomous AI agent that's meaningfully more capable than the AI meeting note tools already on the market.

Ultimately, the biggest question isn't just whether or not GReminders' new assistant can be properly defined as an AI agent, but rather how much AI-driven autonomy is really even helpful in an advisory firm context. With so many of RIAs' processes being systemized and repeatable, there are few uses for technology that can make its own decisions and forge new paths through processes that aren't already defined. And as we've seen with other workflow automation tools, advisors seem to look to their CRM to provide those capabilities. And for those who haven't systematized their processes into defined workflows, the answer likely isn't an autonomous AI agent but a more defined process that can be repeated and automated with simpler (and cheaper) tools. In fact, recent Kitces Research on Advisor Technology shows that automating Client Service tasks is actually the least appealing capability advisors are seeking from an AI-driven tool.

So as more tools inevitably come out that promise agentic AI capabilities – particularly as the market for other AI tools like meeting notetakers gets increasingly crowded and providers seek to differentiate themselves beyond "just" what LLMs can do to summarize alone – it will be worth watching to see not only whether they can deliver on their promises of autonomous AI decision making, but also whether they can find a use case where advisors need a tool that can make autonomous decisions to begin with (and that they trust technology to do for them).

Anthropic's Enterprise-Grade 'Claude For Finance' Threatens Independent Startups Offering AI-Driven Investment Research Tools

Although the explosion in AI meeting note providers has gotten most of the attention among AdvisorTech industry observers over the past couple of years, one category of the Kitces AdvisorTech Map that has also quietly seen a proliferation of new tools since the beginning of the AI boom has been Investment Data/Analytics. Although it was already a crowded category before AI, Investment Data/Analytics has since grown from 35 providers at the beginning of 2023 to 49 today. And while not all of these new tools are explicitly AI-driven, the majority of the newcomers, including tools like Brightwave, Fiscal.ai, Boosted.ai, and ARQA, use AI to trawl through reams of corporate and economic data to generate investment insights on assets like stocks, bonds, and ETFs.

So far, these independent AI investment research tools have been budding because, other than Morningstar and its "Mo" investment research chatbot, few of the existing investment research platforms tools have rolled out substantive AI-driven research features. However, the newness of AI-driven investment research, and of the handful of startup providers offering it, has meant that there has so far been little traction for any of these tools among independent advisors. Among advisors who do conduct their own investment research (rather than outsourcing it to third party investment managers via TAMPs or SMAs or using available models from model marketplaces), the vast majority tend to go with established providers like Morningstar, YCharts, and Kwanti, which don't use (or at least don't emphasize) AI in their research tools.

Put more simply, while AI investment research tools have proliferated, they show little sign of significant adoption among independent financial advisors. Which is likely not as bad as it seems, because independent financial advisors aren't necessarily their only target market. Instead, they may be more interested in pursuing institutional investment managers like mutual fund managers, separate account managers, and hedge funds, that will pay enterprise-tier prices for their solutions, and where a relative few mega-large asset manager clients can make the whole AdvisorTech company sustainable.

This month, however, the standalone AI investment research tools gained a major new competitor with the release of Anthropic's Claude for Financial Services. The new platform is an extension of Anthropic's enterprise-grade Claude specialized for financial research and analysis, plugging into data from sources like FactSet, Morningstar, and S&P, which users can access through Claude's chat interface either by entering their own prompts or by using a financial services-specific prompt library.

The rollout of Claude for Financial Services won't directly affect independent advisors much since it's clearly targeted at the enterprise tier of financial services – as Anthropic's own executives state it, it's meant for organizations on the level of giant hedge funds like Bridgewater or national sovereign wealth funds as an alternative to solutions they might build in-house, rather than for independent RIAs.

However, the indirect effect could be a disruption of the smaller and more specialized AI investment research tools that have come onto the market as of late. Institutional investment firms will no doubt prefer the stability and enterprise-level support that Anthropic can provide compared to smaller and newer startup vendors, which will leave those smaller providers increasingly squeezed out of the institutional market. The only option for those firms, then, might be to go "downmarket" to serve smaller independent RIAs by adapting their capabilities to RIAs' needs (e.g., by focusing more on ETF research, risk modeling, or proposal generation). But the caveat there, however, is that pivoting to RIAs would put those AI investment research tools in head-to-head competition with providers like Morningstar, YCharts, and Kwanti, which currently dominate the market in that space.

All in all, the crop of relatively new AI investment research startups appear to already be in a tough spot, being caught between what seems likely to be an enterprise-dominant Claude, and the independent RIA-leading Morningstar/YCharts/Kwanti triumvirate. Which is reminiscent of the ongoing developments in the AI meeting note space, where an initial glut of standalone AI notetaker providers has been subsequently squeezed by the confluence of established AdvisorTech providers rolling out their own tools (e.g., Wealthbox, Altruist, and most recently Nitrogen) and established "generic" providers rolling out their own finance-specific versions (e.g. Fireflies for Finance). And as AI becomes more established and embedded across other categories of technology, it seems that the same situation will continue to play itself out, as AI is increasingly seen as a feature to be included in the tools that advisors already use, rather than a standalone product in its own right.

EncorEstate Plans Leans Further Into (Tech-Enabled) Human Legal Advice With eLegacy Partnership

Estate planning has long been a part of the financial planning process, but the planning emphasis has shifted greatly over the last 25 years. At the beginning of the 21^st century, the Federal gift and estate tax exemption amount was $675,000 per person, meaning a "modest" $1 million life insurance policy had the potential to create an estate tax issue for an upper-middle-class family and spurred the use of trust-based estate plans like ILITs and bypass trusts to move assets out of households' taxable estates. But as the exemption marched steadily upward over the years to its current level of $13.99 million per person (set to increase further to $15 million in 2026 after the recent passage of the One Big Beautiful Bill Act), the emphasis on avoiding estate tax declined as all but the very wealthiest households fell below the Federal estate tax threshold.

Instead, the emphasis (at least for the mass affluent households whom most advisors serve) has shifted towards ensuring that clients have at least a basic will- or trust-based estate plan in place, since even without any estate tax issues there is still the need to provide for orderly distribution of assets and guardianship of minor children upon a client's death. Without complex trust strategies to navigate, the advisor's role in getting estate plans implemented was most often in connecting clients with a vetted estate planning attorney and spearheading communications between the client and attorney to steer the process to completion.

In the last few years, however, there has been a massive push by software providers (and their venture capital backers) to tech-ify the process of estate document preparation. Providers like Wealth.com, Vanilla, Trust & Will, and EncorEstate Plans have all arisen in recent years with various versions of the same value proposition: Providing a streamlined, digitized estate document preparation process that eliminates the need to vet and refer clients to local attorneys.

But while the end product is essentially the same with all of these providers, they don't all go about creating estate documents in the same way. Wealth.com and Trust & Will have leaned heavily into automating document creation via questionnaires and workflows, while EncorEstate has generally gone in the opposite direction, providing a higher-touch experience with human review included in each plan and the technology serving mainly to smooth communication and handoffs between parties. Meanwhile, Vanilla falls somewhere in between, automating much of its document preparation but also offering human support via its attorney network for complex plans.

The results of these different approaches, however, have been mixed. According to yet-unpublished data from the soon to be released 2025 Kitces Research on Advisor Technology, Trust & Will's highly automated solution focused on middle class and mass affluent clients had the highest average satisfaction ranking at 8.3 out of 10, EncorEstate's higher-touch solution rated slightly behind at 8.0, while Wealth.com and Vanilla, both intended for higher net worth households but largely automating their document creation, lagged behind at 7.5 and 7.1 respectively. The takeaway from the research data is that while advisors with mass affluent clientele might appreciate a streamlined service like Trust & Will to streamline their clients' estate document preparation, for higher net worth clients they would prefer a service with more human involvement like EncorEstate than one that automates the process and minimizes human interaction like Wealth.com and Vanilla.

In that context, it's notable that this month EncorEstate Plans has announced a partnership with the virtual estate planning law firm eLegacy wherein eLegacy's (human) attorneys will provide state-specific review and advice to clients having estate documents prepared via EncorEstate. The key distinction was that whereby EncorEstate had previously provided a more general human review of its estate plans by paralegals and planners who weren't necessarily attorneys, the partnership with eLegacy will provide a more thorough, state-specific review by attorneys who can give actual legal advice. According to EncorEstate's FAQ page, the attorney review is currently available in 16 states plus Washington, DC, and is priced as an add-on fee to the standard estate document plan starting at $200.

The new attorney review option is a plus for advisors who want the more streamlined experience of a tech-enabled estate document creation service, but who might be nervous about the implications of fully automated document creation and the potential that they leave open for the advisor to inadvertently give unauthorized legal advice. Having a human attorney to serve as the reviewer, and take on the legal and financial liability of any advice they give in relation to the estate plan, serves as a useful backstop for advisors to avoid going beyond the advice they're qualified to give, particularly when there are state-specific nuances involved.

At an industry level, the partnership between EncorEstate and eLegacy underscores the contrast between the path that EncorEstate is taking towards estate document creation versus the other providers like Trust & Will, Wealth.com, and Vanilla. What EncorEstate is building is more akin to a tech-enabled service, that uses technology to streamline the process but still keeps human involvement at the core, while the others have skewed more towards full automation of estate document preparation. Which may result in EncorEstate being slightly more expensive on a per-document basis (albeit still less expensive than most fully attorney-created plans), but given that most clients only need update their documents once every 10-15 years, the true difference in cost per year could be negligible.

Ultimately, with the gift and estate tax exemption set to stay permanently at or above its current level (or at least until a future Congress acts to lower it), the emphasis in estate planning for financial advisors will continue to be on simply ensuring that clients have up-to-date documents in order, which creates a market opportunity for providers who can effectively and efficiently fill that need. For many clients with relatively straightforward financial situations, a fully automated solution like Trust & Will may be the best solution; however, for more complex cases where there's still some need for a layer of human review, EncorEstate in its partnership with eLegacy is well positioned to fulfill that demand.

MyStockOptions.Com Launches An Advisor Referral Service As Lead Generation Becomes A New Revenue Stream For Digital Media?

The biggest problem for advisory firms to solve is how to bring on new clients, and the hardest component of that problem getting interested prospective clients on the phone with an advisor. Outbound marketing efforts like paid advertising, social media, and content creation can be incredibly inefficient at drawing interest as they rely on an interested prospective client happening to stumble on the advisor's ad or content at the exact moment they're ready to reach out to an advisor. Hence, advisory firms often happily pay lead generation services significant sums – sometimes exceeding 25% of lifetime revenue per converted client – to funnel leads to them so that all the firm needs to do is have someone available to take the calls from prospects and make the firm's sales pitch.

Meanwhile, the digital media industry is going through a crisis of its own, with advertising revenue plummeting and traffic from Google and social media websites being throttled to keep people on those platforms. Media companies are struggling to find new ways to keep themselves afloat, especially those that have historically relied on advertising revenue that no longer provides the sustainable business model it once did, and to do that they need new revenue streams independent of the advertising dollars that can rise or plummet depending on the whims of Google or Facebook algorithms

For financial media platforms, which often host content that draws retail traffic from individuals looking for solutions to their specific financial problems, one solution to the problem of declining revenue could be to help financial advisory firms solve their own problem of finding prospective clients who are motivated to act. If a person visits a website to find an answer to a specific tax question, for example, they may upon finding that answer realize that what they really need is advice from a professional to help them solve their problem – and if the website has a link to find an advisor who can help them with that particular problem, the person might be motivated right then to reach out and schedule a meeting. And if the person eventually hires the advisor that they find through the website, the advisor can pay the media platform for the referral, and everyone wins: The client has found an advisor who can help them with their financial issue; the advisor has a new source of motivated clients; and the media platform has a new line of business where it can monetize the traffic it already receives by referring interested prospects to the advisor.

In this context, it's notable that myStockOptions.com, which provides in-depth technical content centered mainly around the planning implications of different types of equity compensation, has launched a new directory of financial, tax, and legal advisors. Interested prospective clients can search by location, experience, fee structure and minimums, and specialty; while advisors can pay an annual listing fee from $195 for the "basic" level to $495 for the "elite" level to be included in the directory.

Online media platforms have long leveraged their content to refer consumers to businesses in exchange for either a flat fee or a cut of sales; affiliate marketing has existed online for more than 30 years, while in the financial media context, platforms like SmartAsset, NerdWallet, and Investopedia produce informational content that draws traffic from consumers through search engines and then refers interested users to financial product and service providers like banks, credit card companies, and financial advisors. The difference is that those platforms built their initial business models around monetizing referrals via content marketing, while in the case of myStockOptions, the referral program represents a new business opportunity on top of its ad- and subscription-based model. Which makes perfect sense given that the level of complexity around equity compensation planning is such that a retail consumer who finds their way to myStockOptions.com might quickly realize that they need professional help on the subject, and as a site that is also frequently used by financial professionals themselves, myStockOptions.com is also well positioned to facilitate connecting interested prospects with the advisors who could be best suited to help them.

At a broader level, it raises the question of whether there could be a nascent trend of financial media platforms turning to advisor referrals to create new revenue streams. Advisory firms tend to appreciate the speed with which a media referral program can provide new leads (versus the advisor building out and executing their own market strategy, which can take significantly longer to see any results), as well as the regularity of the flow of leads that can come from those programs. And even though the hard-dollar cost of buying referrals tends to be higher than other marketing channels, the cost still seems reasonable when factoring in the time and uncertainty of outbound marketing methods. So for digital media platforms that already draw traffic from motivated consumers who have problems that a financial advisor could solve, why not monetize some of that traffic by serving as the matchmaker between the lead and the advisor who can help them?

Ultimately, myStockOptions.com's new directory serves to underscore just how much advisory firms have embraced referral and lead generation programs, to the point where any platform with consumer traffic looking for answers on financial topics may find it worthwhile to start up its own referral program. In an industry where so much of the effort of gaining new clients is spent just on getting the attention of prospects who might be interested in hiring an advisor, RIAs are more willing to pay someone to bring leads to them, rather than going out to find the leads themselves, even if it's more expensive to do so. Which puts the media platforms that can draw that attention to begin with in a position where they can capitalize on it. 

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In the meantime, we've rolled out a beta version of our new AdvisorTech Directory, along with making updates to the latest version of our Financial AdvisorTech Solutions Map (produced in collaboration with Craig Iskowitz of Ezra Group)!

So what do you think? Where is the best place for an AI notetaker to 'live', either as a standalone tool or embedded within another technology tool? Are advisory firms' processes systematized enough that there's no need for 'agentic' AI tools? Is it sometimes better to have a fully automated estate document creation process, or should a human attorney always be involved? Let us know your thoughts by sharing in the comments below!