Origin’s New ‘AI Financial Advisor’ Won’t Threaten Human Advisors (And More Of The Latest In Financial #AdvisorTech – October 2025)

Origin Debuts A Low-Fee AI "Robo-Planner" (That Still Won't Threaten Human Advisors)

The reality about the financial advice industry today is that personalized, comprehensive advice is expensive. Per the most recent 2024 Kitces Research on Productivity, a client can expect to pay at minimum $2,500-$3,000 per year for comprehensive financial planning, with many advisors charging annual minimums of $10,000 or more. As a result, the only people with access to personalized financial advice – that isn't tied to the sale of a financial or insurance product – tend to be those who already have either the assets (for those billed on AUM) or income (for those paying hourly or subscription fees) to support the multi-thousand-dollar per year cost for that planning relationship in the first place.

The high typical cost of hiring a financial advisor naturally raises many questions about why the industry hasn't found a way to serve clients who can't afford to pay several thousand dollars or more, who are arguably those in need of the most help with getting their finances on track. One of the most common criticisms is that financial advisors are only willing to serve those who will pay them the most – that as long as there are prospective clients willing to pay $10,000 or more for financial planning, the mass of advisors will always gravitate towards those clients. And there may be some truth to that: The simple law of supply and demand states that the price of an in-demand good or service is dictated by its relative supply, and at the moment there are too few financial advisors to meet the demand from the wealthy and mass affluent, let alone those lower on the economic scale. After all, when financial advisors often cap out at no more than 100 in-depth financial planning relationships, approximately 100,000 CFP professionals means there are only enough advisors to serve about 10 million households, a small fraction of the more-than-130 million households in the US. And so it's almost inevitable that advisors will look to serve wealthier clientele until the demand at the top of the market is satisfied and there's an incentive to look for opportunities elsewhere.

But there's also a deeper story about the pricing of financial advice, which is that it's not only about supply and demand, but about client acquisition cost. In order to serve clients profitably at a more "affordable" price, you need a lot of clients to cover the cost of an advisor and overhead. And while there are challenges in trying to serve comprehensive financial planning clients at high volume (since most advisors tend to cap out at 75-100 clients, which sets a relatively high floor on the per-client fee needed to earn a manageable living), the bigger issue lies in how to market the advisor's services efficiently enough to bring in the necessary volume of clients without breaking the business model. In fact, Kitces Research on Advisor Marketing also finds that the acquisition cost to get a single client is typically more than $4,000 in hard-dollar marketing and time costs of the financial advisor… effectively setting a minimum floor on what advisors must earn in the first year or two just to recover the cost of getting the client in the first place.

Which is exactly the reason why so many efforts to provide low-cost financial planning to the masses (including the robo-advisor movement of the 2010s) have failed: Because scaling the acquisition of low-paying financial planning clients proved too expensive for the amount of revenue generated per client. Or in other words, the less each client is willing to pay for advice, the harder it is to be profitable given the client acquisition costs. And the more clients are needed to sustain the business model (given lower revenue per client), the more expensive it typically becomes to market to each new client at ever-increasing levels of required marketing scale – ultimately leading to a death spiral from which most of the first generation of robo advisors didn't recover.

Against this backdrop, Origin debuted this month what it refers to as "the first AI financial advisor regulated by the SEC". Originally launched in 2023 as a budgeting app, the refreshed Origin is billed as an "always on financial advisor", and combines essentially three pieces of software into one AI-powered bundle. First, there's a budgeting tool where users can monitor their spending and ask the app's chatbot for ways to save money (e.g., by automatically tracking subscription payments and allowing users to cancel unwanted subscriptions through the app). Second, it includes a brokerage app where users can either self-direct their investing (with the AI chatbot facilitating research and market data) or invest in Origin's recommended index portfolios or curated "thematic stock bundles". And lastly, Origin includes a financial planning tool to run future projections and compare different scenarios (e.g., to show the effect of buying a house), with automatically generated planning strategies and recommendations to improve chances of success. All these tools are being offered by Origin for the low price of $1 for the first year, and $99/year thereafter.

At a high level, the debut of Origin's AI financial advisor is a notable new step in the development of low-cost automated financial advice and what can be accomplished with AI. In contrast to the original generation of robo advisors that offered automated investment management with little to no individual financial advice, Origin offers a much more comprehensive package (albeit one tailored to a user base that's presumably younger and less affluent than the average RIA client and is focused on cash flow, growing wealth, and homeownership, rather than retirement, tax, and estate planning). In other words, Origin aspires to truly be an AI financial advisor, with an emphasis on the advice rather than (just) managing investments.

What's also different about Origin compared to the robo advisors of 10-15 years ago is that Origin doesn't claim to have any desire to compete directly with human financial advisors. Whereas robo advisors like Betterment and Wealthfront originally sought to replace financial advisors – with Betterment going so far as to claim in a (quickly deleted) blog post that "Financial Advisors Are Bad For Your Wealth" – Origin states on its own website that its planning tools are "no substitute for personalized advice from a financial planner", and even offers the ability to book sessions with CFP-certified human advisors. So it seems that Origin is less about trying to drive down the cost of advice for everyone and disrupt the human advice model than it is about offering a more full-featured financial planning app for DIYers who weren't necessarily inclined to work with a human advisor to begin with.

But while it makes sense for Origin to focus on the DIY market rather than compete with advisors directly for clients who would rather outsource to a human advisor than figure things out on their own (or choose which app can best figure it out for them), it still remains to be seen whether Origin can overcome the client acquisition cost problem that has plagued mass-market financial planning tools from the beginning. Especially when Origin aims to charge less than the revenue per client that already buried robo-advisors given the acquisition costs. As with the robo advisors, Origin has leveraged technology to commoditize an area of financial advice (investment management in the case of the robo advisors, and budgeting and plan projection in the case of Origin), which leaves it vulnerable to having its margins crushed by bigger competitors who offer similar tools but have lower acquisition costs – as happened with the robo advisors when Vanguard and Charles Schwab began offering their own cheaper automated portfolio management tools that they could cross-sell efficiently (i.e., with lower acquisition costs) to their existing millions of customers. The good news for Origin is that by giving away its software for (almost) free, there isn't much room to be undercut on price. But the bad news is that Origin will still need to figure out how to attract DIY-minded users efficiently enough to support a price that's cheaper than a Netflix subscription. Or at the least will have to substantively raise their fees by 3X, 5X, or 10X just to have a chance to break even on the profitability of serving a client.

The key point is that while it's good that entrepreneurs are seeking out ways to offer better financial tools to individuals who can't afford (or don't want to pay) the cost of a human advisor, it's hard to ignore the feeling that AI planning tools like Origin are bound to learn the same hard lessons that the robo advisors did more than a decade ago: That the high minimums of advisors aren't driven by greed, or even by the cost to service clients, but by the cost to acquire them. And like in the robo advisor era, if competition in the space increases to a point where AI planning tools simply can't keep up the growth rates needed to sustain their current business model, it's possible that we'll see tools like Origin start to pivot away from the direct-to-consumer market and towards more advisor-facing tools. Just as automated portfolio management eventually became embedded in the infrastructure of advisory firms, AI tools – such as chatbots to surface planning ideas and tools that can recall client data buried in past meeting notes – could also become standard as advisors increasingly go "cyborg" to let technology handle more and more of the technical planning tasks so they can focus on their client relationships. But in the meantime, the question will be whether AI tools like Origin can really be the key to making tech-driven financial "advice" affordable to the masses – or if, like the robo advisors before them, they'll find that it's difficult enough to get users willing to pay anything for advice to make the business model viable.

Grantd Buys StockOpter (And Its Content) To Create Its Next-Generation Equity Compensation Tool Instead Of Building Its Own

Equity compensation planning is in some ways an ideal niche for financial advisors. It requires deep technical knowledge of the characteristics and tax treatment of different equity compensation types, from ISOs and NSOs to RSUs, ESPPs, and a host of others, which even otherwise financially savvy individuals might find too overwhelming to handle on their own. And the individuals who receive equity compensation – whether as executives of large publicly traded companies or as early startup employees – tend to be comparatively affluent, making them both willing to and capable of paying for financial advice. An advisor willing to invest in the technical skills needed for equity compensation planning can do well for themselves with the "knowledge moat" that it creates.

However, the same characteristics that make equity compensation attractive as a planning niche make it a difficult category for new software to break into. For many years, tools like StockOpter and myStockOptions, built by experts in the equity compensation field, have allowed advisors to go very deep in their analysis, going beyond just summarizing the current value of vested and unvested stock options to model the tax impact and concentration risk of exercising options at various potential stock prices. This highly technical slant gave StockOpter and myStockOptions a deep user base among equity compensation-focused advisors who value its thoroughness and accuracy – but at the same time it also gave the tools a steep learning curve to use correctly, and introduced a level of "weediness" that left much of the burden of explaining the technology's analysis (not to mention synthesizing it into a clear recommendation) in the hands of the advisor.

In recent years, several new startups have come along to challenge StockOpter and myStockOptions in the equity compensation category. Providers like Trayecto and Gemifi seek to meld equity compensation with comprehensive planning by incorporating the financial and tax impact of exercising options and selling company stock into the client's broader financial situation, while also streamlining the equity compensation planning process itself by automatically importing client data from paper statements or financial institution websites and offering more dynamic scenarios and reports that can be easily adjusted and compared. All of which can help advisors get out of the analytical weeds and deliver more actionable recommendations to their equity compensation clients.

Into this environment came Grantd, which announced this month that it was acquiring the longstanding equity compensation leader StockOpter. What's notable about Grantd is that it's essentially a brand-new company, funded with capital from Edward Jones and TIFIN, which acquired StockOpter to form the chassis of its forthcoming product, an "AI-powered equity compensation planning platform". In other words, rather than building its own equity compensation planning solution from scratch, Grantd started out by acquiring its biggest competitor to rebuild into a new and updated platform.

The acquisition raises a lot of questions, most notably why Grantd chose StockOpter, which is arguably the least "modern" of the equity compensation tools on the Kitces AdvisorTech Map, as the base for its next-generation software. It's hard to imagine Grantd being able to graft an AI-heavy interface onto StockOpter's existing software without rebuilding the whole thing from the ground up. Why, then, wouldn't Grantd use its venture capital to build its own solution rather than buy another one, if it was going to need to invest the resources to do so anyway?

The obvious answer is that StockOpter comes with a deep existing user base (at least deep within the equity compensation niche – in the most recent Kitces Research on Advisor Technology, 6.1% of advisors used a third party software tool for equity compensation planning, and just under half of them used StockOpter). The cost of buying and immediately rebuilding StockOpter might be worth it if it gives Grantd an immediate built-in base of paying customers instead of having to compete for new users with other startups like Trayecto and Gemifi.

But the other part of the equation could be the data that StockOpter brings with it. StockOpter founder Bill Dillhoefer wrote hundreds of articles over the years going into deep technical planning, client communication, sales, and practice management. As an AI-native platform, Grantd needs data to fuel its analysis and recommendations – particularly because on a technically dense topic like equity compensation where accuracy is paramount, it's essential to have trustworthy data to feed into the AI engine to produce trustworthy results. Is it possible that, along with a pre-existing user base, Grantd also valued StockOpter's pre-existing expertise enough to buy it rather than built its own solution?

That question has interesting implications for AdvisorTech as more and more AI-native tools come onto the market. Could we see other new startups arise that opt to buy and rebuild legacy players – along with their user base and data history – instead of starting from scratch? Or was this more of a one-off situation, where the founder of a longstanding category leader happened to be looking to exit, creating the right conditions for the acquisition to work? Either way, it goes to show the value of data in an increasingly AI-driven technology environment, and particularly trustworthy data for technical topics like equity compensation planning. In the old world, it might have been better to build your own product if you thought you could make a better one than the competition. Today, if the competition has the data you need to make your product better, it might be better to buy the competition – and the data – even if you still have to build the software from the ground up.

Intelliflo Spins Off Redblack, But Does Anybody Pay For Standalone Rebalancing Software Anymore?

In order to manage investments for their clients, financial advisors need a minimum of three things. First, they need a custodian that both serves as a broker-dealer to execute client trades as well as the custodian keeping the ledgers of client accounts to verify their holdings, position values, cost basis, etc. Second, they need a trading and rebalancing tool that can monitor client portfolios against their asset allocation targets, calculate trades when rebalancing occurs, and provide a trade order file for the custodian to execute (or send the trades directly to the custodian directly). And third, the advisor needs a portfolio accounting and reporting tool that can calculate and generate reports showing the client's investment performance, as well as calculate AUM fees accurately to align with the advisor's fee schedule. There are other categories of software under the portfolio management umbrella as well – investment research tools, held-away assets and account aggregation, risk tolerance questionnaires, etc. – but those three are essentially what's needed to get off the ground.

Originally, the technology that came along to perform these essential investment management functions evolved separately from each other. 20 years ago, an advisor would have one tool for their performance reporting and another for trading and rebalancing, in addition to their custodian which likely had few technology tools of its own. But starting in the mid-2010s, a consolidation of portfolio management technology began to occur, starting with iRebal's acquisition by TDAmeritrade. Providers like Orion and Black Diamond, which had originally arose as performance reporting-only tools, began to build or buy their own integrated rebalancing tools. Others, like Morningstar Office and later Advyzon (from the same team that had originally built Office), built all-in-one portfolio management tools from the ground up. But in either case, where it was once the norm to use multiple tools for implementing and monitoring investment management, it was now becoming increasingly common to rely on a single tool for rebalancing, trading, performance reporting, and billing (although in most cases the custodial function remained separate from the others for the actual trade execution).

One of the early standalone rebalancing tools was RedBlack. In late 2019, RedBlack was acquired by the asset manager Invesco as part of a buying spree of advisor technology aimed at boosting the distribution of Invesco funds through the RIA channel (and the tail end of the broader trend of consolidating standalone rebalancers, where RedBlack was one of the last to be acquired). Eventually, Invesco consolidated its various acquisitions (including the robo advisor Jemstep and another rebalancing tool, Portfolio Pathways) under the Intelliflo brand as an all-in-one portfolio management solution. The problem, however, was that Intelliflo was primarily a UK brand with little penetration or recognition in the US. And so while Intelliflo found solid usage overseas, it had little traction in the US, with the most recent Kitces Research on Advisor Technology finding it with a less than 0.5% adoption rate among advisors.

This month, however, the news broke that Invesco is selling its Intelliflo business to the PE firm Carlyle. In the process, Intelliflo is also separating its UK-focused business from its US side, where the US rebalancing software has been rebranded back to its original RedBlack name.

In other words, RedBlack is back on the market as a standalone trading and rebalancing tool. And after all the consolidation and building of all-in-one portfolio solutions over the years since it was first acquired, RedBlack becomes one of the few remaining standalone rebalancing tools left on the Kitces AdvisorTech Map. In fact, of the eight remaining companies in the Trading/Rebalancing category, one (iRebal) is no longer available as a standalone tool following Charles Schwab's acquisition of TDAmeritrade; one (Blaze Portfolio) is set to wind down at the end of 2025; two (Smartleaf and Alphathena) are more about personalized direct indexing than generalized rebalancing; and one (SEI LifeYield) is billed as a "householding" tool for complex multi-account and multi-custodial portfolio situations. Leaving only RedBlack, Flyer Financial Technologies, and SoftPak as the three 'true' standalone rebalancing solutions left on the market!

Which begs the question of which RIAs really need a standalone portfolio rebalancing tool in 2025? There has been plenty of debate over the years between proponents of multifunctional "all-in-one" tools versus "best in class" standalone solutions, but the evolution of portfolio management technology over that time has clearly shown that advisors prefer a single tool for rebalancing, reporting, and billing, both for the depth of integrations and often simply because it's less expensive than buying each separately. And even if advisors did decide to adopt a standalone rebalancing tool like RedBlack, they'd still need to pair it with a standalone performance reporting tool, which is itself a category that has shrunken greatly over time as its providers have been consolidated into more holistic portfolio management platforms.

It appears there are essentially three paths forward for tools like RedBlack. They could either develop some trading capabilities that are more sophisticated and complex than what the existing all-in-one tools like Orion, Black Diamond, and Advyzon can do – e.g., something in line with Smartleaf and Alphathena's direct indexing solution or SEI LifeYield's householding tools – which would involve finding some part of the market that isn't being served capably by other solutions and building in that direction to differentiate itself. Alternatively, RedBlack could build out its performance reporting capabilities to more directly compete with the all-in-one portfolio management solutions (effectively becoming one itself) – which is a daunting proposition given how fierce the competition between the existing tools, and yet there could be room in the market for a 'lighter' portfolio rebalancing tool that doesn't include CRM, client portals, risk tolerance, and the myriad other tools that many all-in-ones pack into their solutions. Otherwise, RedBlack could find itself facing the third alternative scenario, which is being re-acquired – either by an existing tool in the portfolio management category, a standalone performance reporting tool (e.g., AssetBook or EZFol.io) that wants to acquire the capabilities to become a full-fledged portfolio management solution, or by another asset manager looking for an advisor-facing solution to distribute its products.

In the end, though, what's striking about how portfolio management technology has evolved since RedBlack's original acquisition is how, despite the high cost of independent all-in-one portfolio rebalancing tools (which can run into tens of thousands of dollars annually even for a medium-sized advisory firm), advisors have largely rejected the idea of AdvisorTech solutions owned by asset managers, including not only RedBlack but also BlackRock's version of Future Advisor, which it shut down in 2023 eight years after buying the robo-advisor platform. Although advisors certainly factor cost and ease of use into their technology decisions, independence – and being free from entanglements from asset managers seeking to boost distribution of their own products – is clearly a red line that many independent advisors won't cross when they're obliged to act in their clients' best interests.

Wealthfeed Partners With AdvisorStream To Combine Targeted Prospect Research With Marketing Automation

For advisory firms, there's a significant distinction between prospecting and marketing. In a broad sense, prospecting can be defined as finding and proactively reaching out to people who would potentially make for a good client fit, while marketing is defined as promoting the firm in a way that will cause people to reach out unsolicited. Traditionally, these have been viewed largely as separate business development channels with their own technology and services to support them, with tools like WealthFeed, FINNY, Aidentified, and WEALTHAWK helping with prospect research and outreach, and tools like FMG Suite, Snappy Kraken, and AdvisorStream providing marketing automation solutions for advisors.

But there are cases when prospecting and marketing blend together. A cold call to a prospect is likely to result in a "no", but the sales process doesn't necessarily have to end there. If the advisor can continue marketing to the prospect in some form, then they may be top of mind when the prospect finally is ready to hire an advisor, which makes it potentially worth continuing to invest in marketing even for prospects who didn't become clients the first time.

Which is why it's notable to see the news this month that the prospecting solution WealthFeed is partnering with the financial technology behemoth Broadridge. Under the terms of the deal, Broadridge will take a minority stake in WealthFeed, while WealthFeed will begin to offer Broadridge's AdvisorStream marketing automation tools within its platform.

The partnership makes sense, as while WealthFeed offers innovative ways to search for and evaluate prospects, it hasn't up until now offered much in the way of methods to market to them. The platform does include a clever tool to create (robotically) "handwritten" notes to mail to prospects, but after that initial outreach, advisors were on their own with figuring out how to market to them further. With a combined tool to both identify prospects and subsequently market to them after first contact, WealthFeed can potentially improve its ROI by making it more likely that a prospect found through WealthFeed will eventually become a client, even if they don't immediately say "yes".

From an industry perspective, the deal is notable in that it shows some very early signs of what could perhaps become a consolidation trend in the prospecting, marketing, and business development areas of advisor technology. Just in the past year multiple AI-driven prospecting tools have come online, including not just WealthFeed but also Cashmere, FINNY, Aidentified, TIFIN AG, WEALTHAWK, and Equilar ExecAtlas. It seems increasingly unlikely that all of these tools can survive on their own, especially given that, according to Kitces Research on Advisor Marketing, fewer than 5% of advisors even engage in outbound cold prospecting to begin with. At the same time, digital marketing tools have been in growth mode, including most notably FMG Suite, which just last month was acquired and provided with fresh capital by PE firm GTCR and which could conceivably buy one of the aforementioned prospecting solutions to integrate into its marketing platform. It would be unsurprising, then, to see the partnership between Broadridge and WealthFeed as the start of a potential exit strategy whereby Broadridge could eventually buy WealthFeed outright (which also takes Wealthfeed off the table as a potential acquisition target by FMG, though there are still plenty to choose from).

The bottom line is that the deal between Broadridge/AdvisorStream and Wealthfeed signals a potential shift away from prospecting being treated as a standalone sales channel to becoming a part of a more holistic business development process. If an advisor can hold onto a prospect's attention after the initial outreach, even when the prospect says "no" the first time, that's potentially much more valuable than a cold call that's forgotten as soon as the advisor hangs up the phone. In which case a tool like WealthFeed – which can narrow down the list of prospects to target, facilitate the initial outreach, and automate the drip marketing to them after that first call – is well positioned to help facilitate the shift from standalone prospecting to a more integrated strategy.

$50 is the new $120?: Price Compression Comes To AI Notetakers As Altruist And Wealthbox Debut Their Less Expensive Solutions

When AI notetaking tools for advisors first came onto the scene in the last 1-2 years, advisors essentially had two options. Either they could use a "general-purpose" tool like Fireflies, Fathom, or Zoom's native AI tool, which were free for their basic versions or, at most, around $20 per month for a paid tier; or they could use an advisor-specific option like Jump, Zocks, or Finmate AI that was more tailored to advisory firms via features like integrations with CRM and other tools, but initially cost much more than the generic options at around $120 per month. And for a while, it was an either/or proposition: pay a little (or nothing) for a generic notetaker, or $120 for an advisor-specific version.

For some advisors, the cost of an advisor-specific notetaker really was worth the big gap in price. In the most recent 2025 Kitces Research on Advisor Technology, the top two advisor-specific notetakers (Jump and Zocks) garnered a combined 12.8% adoption rate, while the top two generic tools (Zoom AI and Fathom) added up to just 7.6%. In general, advisor-specific tools also rated higher in advisor satisfaction than the generic options, indicating that advisors felt like the extra cost was indeed justified by the advisor-specific features offered by the likes of Jump and Zocks.

But as advisor-specific AI notetakers have proliferated, the burning question has been what would happen when other advisor technology tools started to launch their own embedded AI notetaking features. For example, if a major CRM platform introduced an AI notetaker of its own, it could likely promise the most seamless integration and user experience of all notetakers for users of that CRM. And because an existing platform like a CRM already has a built-in user base that it can cross-sell to at little cost, it could severely undercut the pricing of the standalone AI notetakers on the market – potentially all the way down to $0. Which means that the standalone tools would need to either cut their price or significantly enhance their value proposition in order to stay viable.

Now we are finally starting to see that scenario play out, and it appears that standalone AI notetakers are indeed starting to feel the effects of price compression amid the presence of cheaper alternatives. The last month has seen the rollout of Altruist's Hazel (the AI notetaker that Altruist revamped and relaunched after acquiring Thyme earlier this year) and Wealthbox's built-in AI notetaker, both of which are priced at around $50 per month – well below the cost of standalone advisor-specific tools like Jump and Zocks. Both tools are designed to integrate deeply with their respective parent platforms (although Hazel is notable also available as a standalone option, even for advisors who don't custody at Altruist), giving them a significant additional advantage over other standalone options.

In response, we're already seeing what appears to be some concession on price from the standalone advisor-specific notetakers. Jump, Zocks, and Finmate AI have all introduced tiered pricing structures, with more basic features starting at $75 (for Jump), $67 (for Zocks), and $76 (for Finmate AI) per month. At the same time, the standalone tools have worked to pack more features into their higher-price tiers: For example, Jump's $120/month plan features meeting "scorecards" for advisors to evaluate their (or their employees') meeting skills, and Zocks' $184/month tier can create automated replies to client emails.

For advisors, both the good and the bad news is that there are now more options than ever in choosing an AI notetaker – good in that there are multiple options to be found, amid a range of price points from 'free-ish' (for most generic options) to $50-$75 (for Hazel, Wealthbox, and the standalone notetakers' basic tiers) to $120+ (for the standalone notetakers' full-featured tiers), but bad in that advisors need to get ever more granular in how they evaluate and decide on an AI notetaker given the expanding number of options available. Whereas one year ago advisors only needed to decide whether they wanted a generic notetaker or a more expensive advisor-specific option, with a just handful of options to evaluate after narrowing it down, advisors now have to decide between generic notetakers, tools that are integrated in their existing platforms (like Altruist, Wealthbox, and in all likelihood more to come in the near future), and multiple tiers of standalone advisor-specific options. All of which are continuing to shift rapidly as technology providers churn out ever more notetakers while existing notetakers roll out new options almost daily.

From a broader perspective, though, what's clear is that the industry hasn't yet – at least until now – settled on what an AI notetaker should cost. The $50 price of Hazel and Wealthbox feels like a line in the sand, drawn by providers with the scale to price more or less on their own terms, and around which the existing standalone tools will need to realign their own pricing and value proposition. If $50 is indeed the new $120 for AI notetakers, then the providers still charging $120 will need to become more than "just" an AI notetaker to justify their existence – for example, to build their own CRM onto the notetaking chassis to encompass the advisor's whole client and relationship intelligence functions (before all of the CRM platforms follow suit from Wealthbox and build their own notetakers, squeezing out the standalone providers entirely).

Ultimately, while we're far from at an end to the saga of AI notetakers, and no one knows exactly where things will end up, the launch of Altruist's and Wealthbox's solutions feels like a shift towards a future where AI meeting notes live within an integrated solution rather than as a standalone piece of technology. Whether that means that the current standalone tools grow to extend beyond their meeting support functions, or other existing advisor technology platforms keep rolling out their own notetakers to squeeze out the standalone competitors (or some combination of both) remains to be seen. But in either case, the current crowded landscape of standalone AI notetakers might not be long for this world.

New Technology Spotlight: Slant's AI-Native "Relationship CRM"

CRM software has a long history as a form of digital Rolodex. In a general sense, CRMs began mostly as a way to electronically keep track of customers' contact information and their history of interactions with the business (i.e., the first generation of CRMs really was a digitization of actual Rolodexes). But over time, CRMs gradually expanded to capture more and more aspects of the customer (or in the advisory firm context, client) relationship: Archived meeting notes and emails, relationships with third party professionals like accountants and attorneys, workflows and task management for team members to handle client-related projects, and tagging clients and prospects for grouping and reporting purposes have all become standard aspects of advisor-specific CRM tools.

But while the traditional CRM structure works fine as a central hub of client information and a historical repository of interactions, it often has shortcomings when it comes to… well, managing client relationships. For one thing, there's no way for advisors to pull up important historical information without actively going to look for it: For instance, if a client noted in a prior meeting that they have employer stock options vesting on a certain date, the advisor would need to go searching for that specific meeting note to look up that date and ensure that they follow up with the client when the options vest. And in an advisory firm context where a client and advisor might meet 1-2 times a year, and have numerous other emails, phone calls, and other interactions in between, over the course of 10-20 years (or more), the sheer amount of client information can make it so that important details can quickly get buried and forgotten. For which at best, advisors have to re-surface the information by adding custom fields to their CRM to make the details more easily referenced… leading to an inevitable bloat of custom fields in the advisor's CRM interface over time.

However, situations with large amounts of text-based information that need to be scanned, summarized, and have the most important points pulled forward tend to be remarkably good use cases for AI. What if, instead of having to proactively search for relevant information, the CRM automatically organized the client's file with the most important information and action items on top (with everything else easily searchable on demand via chatbot)? And automatically generated a list of actions for the advisor to take based on their client interaction history alone (e.g., scheduling a meeting with one client, replying to an email question from another, and reviewing a financial plan projection for a third client)? And automatically incorporated new information after every client meeting? In other words, what if, by making use of the things that AI is good at, it was possible to reshape the CRM experience so it's actually centered around managing client relationships rather than simply recording them?

This is the goal of Slant, which recently launched, billing itself as a new kind of "relationship CRM". In a nutshell, Slant is a CRM that layers on AI in different ways to better surface information and automate tasks with the aim of helping the advisor spend less of their day-to-day time on searching for information and more time interacting and developing client relationships. For example, Slant captures certain details about clients – e.g., information on family members, goals, and important concerns – as "memories", which the system recalls and brings forward in relevant contexts like preparing for a meeting or asking questions of the built-in chatbot. This feature eliminates the need to create custom fields to capture notable client information – Slant simply flags those details in meeting notes and other interactions, and brings them to the surface whenever necessary.

Additionally, Slant comes with its own integrated AI notetaker – not as an add-on feature like Wealthbox's recently debuted notetaker, but as a core feature of the platform – which automatically logs meeting notes in the client's record and also generates follow-up emails and action items. It uses the data in its system from client meetings and other interactions to generate "nudges" for the advisor to take certain actions (e.g., replying to emails, completing follow-up tasks, and reaching out to clients), and even to take certain actions on its own, such as scheduling client meetings. All of which results in a CRM that is more expensive than average – at $150 per month, Slant is exactly double the cost of Wealthbox's standard pricing tier – but when factoring in the cost of adding an advisor-specific AI notetaker for $50 (for Wealthbox's built-in version) or $75-$120 (for a standalone advisor-specific notetaker), the cost difference narrows significantly or even ends up with Slant being less expensive than comparable options.

In effect, then, Slant is what a CRM looks like when it is entirely built around AI, and uses the technology in ways that actually center the CRM experience around the advisor-client relationship. Which is a very different vision of CRM than the "digital rolodex" version that has been predominant for most of its history – because while it's one thing to increase the breadth and depth of data captured about every client as CRM tools have consistently done over the years, it's another thing to build it from the bottom up to take advantage of the capabilities of AI for a more relationship-focused experience. As with all AI technology, it will take time to know if what Slant is building actually lives up to its aspirations – the varying quality of LLMs makes it so it's almost impossible to know without trying out the software in various contexts – but it's nevertheless refreshing as a concept, and the thoughtfulness that Slant has put towards using AI to build features that support client relationships should be the model for any advisor technology provider building around AI.

One thing that Slant notably doesn't sell itself on, at least for now, is the amount or quality of its integration with other software. Other than email and calendar systems, Slant doesn't appear to integrate with other advisor technology tools such as financial planning or portfolio management somewhere. Which could be an issue for advisors who rely on such integrations to manage their client data across platforms – for those who see their CRM as their client data hub, a tool like Slant, where much of the data is stored in an unstructured format rather than in standardized fields (which still is the norm in most software), would require a rethinking of not just their CRM, but of their entire tech stack. It's possible that that would be simply too far a leap for some advisors, who might rather stick with a tool like Wealthbox which can still serve as a central data repository if it means that it won't break their connection with all of their other software – although it's worth watching to see if Slant starts to build out its own integration capabilities (and potentially start to weave that data into its AI models).

Still, the future that Slant helps to envision is an enticing one, where CRMs can help better support advisors in keeping on top of their clients' needs. In the current environment, where many advisors feel fairly lukewarm about the CRM tools that they use (with the latest Kitces Research on Advisor Technology finding advisors rated their satisfaction with their CRM tools at an average of 7.6 out of 10), there's an opportunity for a provider that can build a CRM that better suits advisors' needs. In the end, it's not (just) about technology that helps advisors not just work faster and more efficiently, but about helping them to serve their clients better by following through on promised actions and remembering the information that matters – which is what Slant has positioned itself to do by thoughtfully using what AI does well to put client relationships first.

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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? Can Origin find success serving a mass market user base, or will it need to pivot to serving advisors as previous "robo" tools have done? Is it still worth paying $120 per month for an AI notetaker when there are other advisor-specific options for $50? Is a more relationship-focused CRM like Slant better than the existing options, or would you rather wait until it can integrate with other tools? Let us know your thoughts by sharing in the comments below!