Two 27-year-olds raise $3.6 million to mine 'real-time,' high-net-worth RIA leads, with AI doing double duty to wire client-advisor chemistry

A tiny two-year-old startup with young Berkeley, Harvard and Caltech grads just raised $3.6 million in seed funding from prominent VCs who are wagering its plan to use artifical intelligence (AI) in a new way to match big RIAs with big investors, has legs.

The Los Angeles company, called “Cashmere,” uses machine learning to mine data from social media and other websites to both find, then divine human qualities of advisors and high-net-worth and ultra-high-net-worth investors – $10 million and up in assets. 

“We look for characteristics where two people are a great match for each other - that's where we're leveraging AI,” says co-founder Farbod Nowzad, 27

The AI zeroes in on significant life events, such as a divorce, marriage, a move, promotion, or sale of a business. 

For instance, LinkedIn publicly lists promotions and new jobs, and data sites can reveal commercial-backed mortgages and refinancing.  

“We can identify these moments in real-time,” says Nowzad.

“It was an opportunity we saw from a technology standpoint to bring intelligence and insight into how people discover potential new clients and how to help engage them the most.” 

Right now, cold outreach usually means only 2% to 3% engagement rates." 

Nowzad says his firm's conversion rates have been as low as 20% and as high as 70%.

“Our goal is to drive that up.” 

Marriage making

Nowzad, a Berkeley graduate and the program's first data science graduate, and Govil, a Caltech graduate, founded a newspaper together at Sacred Hearts High School in Atherton, Calif., before going into business together.  

They raised nearly $1 million, initially, before they'd finalized their concept. 

“It's kind of like Zoom with a sprinkle of Hinge for wealth management,” Nowzad says, referencing the virtual meeting platform and Hinge, a popular dating app. 

Whether Cashmere zooms may hinge on whether its honeymoon with RIAs, investors and VCs carries over to a solid marriage.

“There’s essentially no other industry where you can acquire a non-enterprise client that generates $50k to 100k per year in revenue and sticks around for 20- to 30-years,” Nowzad says in a statement.

“Despite this, the industry does not have the infrastructure and intelligence layer to consistently identify who the best clients are, match them with the right advisor at the right time…"

Competitors abound

Though Cashmere's prospecting service has some fresh ideas, it faces some big obstacles to success – not least legacy firms and startups with similar concepts and approaches.

Founded in 2022, Cashmere isn't the first to enter the fray, says Andrew Besheer of consulting firm Besheer and Associates LLC.

“I think advisors often struggle to prospect for clients. That said, I don't think the industry necessarily lacks the infrastructure to support advisors prospecting clients, he says. 

"I certainly don't think Cashmere is a ‘first-mover’ even in terms of AI-enabled prospect matching.”  

Aidentified, Finny and Wealthawk are among firms offering similar services, he notes. 

“All… look and feel a lot like Cashmere if you look at their websites. And then I can think of folks like Anasova and SmartAsset who use their proprietary – non-AI – matching methodologies to help advisors build practices. 

"And then I can even think of firms like Zoe Financial that are assisting advisors in prospecting as part of a broader platform of services,” Besheer says. 

Ready market

But Cashmere's approach is different, Besheer acknowledges.

“Cashmere appears to be using AI to go out and actually identify prospects based on data around life events, etc. that identifies them (the civilians) as being likely to need an advisor,” he adds.  

"I think the number of players in the space clearly highlights that this is something that both broker-dealer advisors and RIA’s will pay for.

"I think the converse question is…are there already too many of these players, and does there need to be a round of consolidation to actually get a couple to some real scale?” 

“It is a lead generation tool, but it seems very different from traditional platforms like SmartAsset,” says Will Trout, director of the Securities & Investments practice at Datos Insights. 

“SmartAsset primarily relies on content marketing and a large online presence to attract clients. Cashmere is really an AI-driven, end-to-end platform focused on prospect identification and personalized outreach and engagement.” 

Envestnet has also long pursued a strategy of using Yodlee big data to identify investors in transition, hence open to a good RIA or IBD rep pitch. Trout sees a difference with what Cashmere is doing.

“Aggregation platforms like Yodlee and Plaid contain a lot of data, but mostly on existing clients,” Trout says. “This data is often generic and hard to translate into compelling communications, and it doesn't do much in terms of identifying common characteristics across a large set of clients.”

Relationship warming

Advisors will pay for prospects. Clearly, this is something that many feel is not a skill set that is one of their primary strengths, so there’s opportunity, Besheer says.

"However… it’s unclear what the secret sauce is that will ultimately differentiate the winners from the losers," he adds. 

Cashmere will plumb LinkedIn, which publicly lists promotions and new jobs, and data sites can reveal commercial-backed mortgages and refinancing.  

The AI is also used to scrutinize RIAs and cross-reference them with the plum wealth management candidates – then even plug the leads into an advisors' customer management system (CRM).

“We look for characteristics where two people are a great match for each other - that's where we're leveraging AI,” he says.

 “There are some gray areas in how you might access two profiles and if they fit each other. 

You can't write hard and fast rules for every possible combination. Leveraging AI and machine learning algorithms is how we ultimately do that.

“Once we're confident that we can back into LinkedIn profile and get contact information and address, and then get the home value, and that's a great indicator of wealth," Nowzad says. 

“If you grew up in Northern California, and so did the prospect, and you want to U.C. San Diego, those are connections that can help turn a cold relationship into something that is warm," he adds.

Mining quality data

“Data quality and accuracy matter a lot here," Nowzad says. 

"In data science, errors, missing information, and inaccurate insights compound on each other, making leads unusable. We are investing a lot in data quality and generating accurate insights/predictions that have an impact,” he says. 

Overall, Nowzad says the wealth industry typically uses outdated ways to find clients. 

“The processes to acquiring new clients are antiquated,” Nowzad says. 

"The reality is that firms today don't have much ready access to high quality information on prospects, particularly on the next-generation and high-net-worth individuals so attractive to advisors," says Trout.  

"They aren't able to generate much in the way of personalized outreach content either. 

"I like in particular the way Cashmere's smart matching algorithm uncovers shared connections between prospects and advisors, making introductions feel more personal.

Finding a fit

Helping RIAs and advisors to be more efficient in finding like-minded clients is where Cashmere stands out, says Jeff Reitman, general partner at Canapi Ventures, in a statement.  

“Its platform equips firms with the intel they need to efficiently acquire and retain high-value clients, and their team has already begun working with advisor teams at some of the largest banking platforms.

Nowzad says Cashmere has a number of banking clients and nearly a dozen RIAs, ranging from solo practitioners to larger firms. The company is earning revenue, but he declined to say how much, or if Cashmere has netted a profit yet. 

Data shows that more than 60% of clients switch advisors because it wasn't a good fit, or there was a mismatch in expertise. 

“It's really about enabling the discovery of the right people and giving them insight on why they're a great fit and how you should be engaging them.” 

Cross-selling

Right now, Cashmere uses a credit system. Large firms and RIAs pay a monthly subscription, and they get access to a certain number of prospects. 

He said a larger mid-sized RIA would likely pay close to six figures on an annual basis, and a solo RIA would pay as low as $1,000 a month for access to 500 prospects. 

“As we build more automation, we'd love to create an outcomes-based model,” he says. 

Cross-selling is a strong opportunity for the firm, too, Nowzad says. Cashmere helps to match up banking clients with wealth management products. 

“We think the interesting opportunity would be if you have an existing relationship with a banking customer to cross sell them into wealth management,” he says. 

But Cashmere doesn't do any selling.

“It's not like we deliver a lead directly to the door. They'll have to do outreach and engage them themselves,” he says.

Hiring staff

Fintech venture specialist Canapi Ventures led the funding round for the eight-person Los Angeles company, after its clinical trails proved promising, according to Nowzad and co-founder Eshan Govil, also 27.

Canapi most recently invested in Capitalize, a firm that makes 401(k) rollovers roll. See: Capitalize inks 'deep, multi-year' deals with Schwab, Betterment and Robinhood to mine 401(k) assets, and $19 million VC round follows

Benchstrength, Plug and Play, The House Fund, Courtyard Ventures and others are also participating in this round, which Cashmere will use to bolster its eight-person staff and allow them to hire more engineers.

The firm has already used the money to hire Sean Cheng, 28, a Harvard PhD graduate in applied physics, as head of machine learning.  

Nowzad is focused on the business side, including sales and marketing. Govil, a two-year engineer at Goldman Sachs, will focus on software engineering. 

Cheng is focused on algorithm and model development and building proprietary scoring to match prospects with RIAs, Nowzad says. 

I do think we'll see adoption among RIAs, particularly if the integration into the CRM (and existing lead lists) is as seamless as Cashmere says it is. Given the firm's backers and pedigree, I would not bet against them," Trout says.