The Front Lines
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Bassam Chaptini.
CEO & Co-Founder · Avantos AI
Bassam Chaptini is the Co-founder and CEO of Avantos. Previously, he was a Founding Member and Chief Technology Officer at Unqork, where he led the company’s technology strategy and innovation. Before Unqork, Bassam was a Partner at McKinsey & Company, where he provided strategic guidance and technical expertise to drive digital transformation for clients.
Guest
Bassam Chaptini
CEO & Co-Founder
Company:
Avantos AI
Location:
United States
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How Avantos AI Is Replacing the Patchwork of Tools That Financial Services Firms Have Relied on for Decades

Before Avantos AI had a name, it had a design partner.

Bassam and his co-founder Rabih didn't launch the company and then find customers. They built the product in stealth with Mercer Advisors — one of the largest wealth management firms in the country — deployed it, measured the impact, and only founded the company once the results were real. In a recent episode of BUILDERS, Bassam Chaptini, Co-Founder and CEO of Avantos AI, walked through that journey: how a 20-year-old problem in financial services finally had the right technical conditions to be solved, and how Avantos went from a stealth build to design partnerships with Guardian Life, Vanguard, and SEI — without a marketing function.

The Problem That Kept Repeating

Financial services firms don't have a data problem. They have too much data. What they've never had is a way to model a client relationship in full — the client, the team servicing them, and the complex products they hold — as a single connected picture.

The tools firms were using were never built for it. As Bassam puts it: "CRM is built to do sales, not servicing." Task managers were built for operations. Portfolio systems gave advisors one slice of the equation. The result was what Bassam calls the "swivel chair" problem — advisors bouncing between four platforms to complete a single workflow, with everything else on paper. "These platforms really were not built to maintain a client relationship. They were built to do a very specific function."

Bassam and Rabih had watched this pattern across 20 years and two companies. The white space was clear. The entry point wasn't.

Let the Buyer Resolve the Market Question

Wealth management, insurance, banking, capital markets — the dysfunction existed across all of them, and Avantos had all four on the table simultaneously. What broke the tie wasn't analysis. It was Mercer Advisors showing up with a mandate.

"We had a design partner coming in, a big wealth manager, Mercer Advisors, who from the get go were very excited about building a new way to service their clients." The president of Mercer came in direct: what they had in place didn't work, and they wanted to build something new. Bassam and Rabih partnered with them quietly — no launch, no announcement — building and deploying until the results were unambiguous. "Once we started getting the impact, the real impact by deploying it, is when Rabih and I decided to found the company back in September 2024."

The sequence matters: Avantos's beachhead wasn't selected from a spreadsheet. A buyer arrived with urgency and co-built the answer with them.

The Architectural Decision That Unlocked Everything

During that design partner phase, Avantos hit a wall that clarified the nature of the problem.

They started with relational tables — the standard approach to data modeling. It collapsed immediately. "It gets out of control very quickly. It doesn't matter how you structure it. It gets out of control very quickly. Hence why people revert to paper a lot of the times."

The core issue: a relational model can represent client data or team data or product data in isolation. It can't represent the relationships between all three simultaneously without the schema becoming unmanageable. So Avantos moved to a knowledge graph — a technology built precisely for modeling complex, interconnected entities. "It literally contextualizes all the data and you can have very complex relationships between those data elements without breaking your model."

The architectural choice had a second-order effect that wasn't immediately obvious: knowledge graphs are natively compatible with AI agents. Agents require rich contextual data to operate — the same contextual structure that a knowledge graph is designed to produce. The infrastructure decision made for data modeling reasons turned out to be the right foundation for the AI layer Avantos was building on top of it.

GTM Without a Marketing Function

Avantos reached Mercer Advisors, Guardian Life, Vanguard, and SEI without a marketing team, without inbound, and without demand generation. Bassam is specific about why that held: "Going to enterprise and asking to be a foundational layer does not require marketing. It requires you to know the client super well. It requires a network for you to come in and be credible, obviously with the track record you have."

The expansion strategy after wealth management followed the same logic. Rather than evaluating verticals in the abstract, Avantos used their Series A to recruit design partners in each adjacent market they planned to enter — Guardian Life for insurance, Vanguard for brokerage-to-wealth cross-sell, SEI for banking. The entry mechanism was consistent across all three: each institution already had an established wealth business, making wealth the known starting point and the adjacent product the expansion target. "We're picking the design partners that are very strategic and using wealth to expand into the other products."

Selling AI Into a Conservative Industry

Enterprise buyers in financial services come to Avantos with two concerns. Data isolation — how client data is segregated and protected — is the first. The second is automation anxiety: what happens to the people.

Bassam's answer to the second concern is a reframe. In wealth management, the binding constraint isn't headcount — it's advisor capacity. There aren't enough advisors to service the clients firms want to reach. Avantos doesn't threaten that capacity; it expands it. "The first thing that people ask us: how much productivity you increase from an advisor perspective? And typically we do increase it... from our measurement, about 30%. We measure it by advisor to client ratio — how many more clients you can serve as an advisor by using our platform versus not using it."

That metric does specific work in the sales conversation. A 30% increase in advisor-to-client ratio means incremental clients served, which means incremental AUM, which means incremental revenue — not cost reduction. In an industry where AI triggers job displacement fears before it triggers curiosity, leading with a growth outcome rather than an efficiency story changes the frame entirely.

The category name remains an open problem. "CRM" was already taken and actively misleading — Salesforce had captured the term and turned it into a sales tool. Bassam's solution was to stop chasing a label and lead with the pain: client onboarding and servicing in financial services is broken, and buyers recognize it without needing a category to frame it. "We show up and we say we focus on client management, particularly onboarding and servicing. Our clients immediately get it."

When the problem is acute enough, the category can wait.

Six takeaways from this conversation.

Actionable for Fintech and Banking founders

  1. Let the buyer who shows up first tell you which market to enter.
    Bassam and his co-founder had wealth management, insurance, capital markets, and banking all on the table simultaneously. What broke the tie wasn't analysis — it was Mercer Advisors arriving with a clear mandate. The president of Mercer came in saying what they had in place didn't work and wanted to co-build something new. Avantos partnered with them in stealth to validate the platform before officially founding the company. When a specific buyer shows up with that level of urgency and is willing to build with you, that's a stronger signal than any market sizing exercise. The analysis can follow.
  2. Relational tables will eventually break your data model — know when to reach for a graph.
    When Avantos first tried to represent the three-way relationship between clients, the service team, and the products clients hold, they started with traditional relational tables. Bassam is direct about what happened: it got out of control quickly regardless of how you structure it, which is why firms revert to paper. The knowledge graph solved it because it can represent arbitrarily complex relationships between data entities without the model collapsing — and as a side effect, it turned out to be natively well-suited for AI agents, which require rich contextual data to operate effectively. For founders building in any domain with deeply interconnected entities, this is a meaningful architectural lesson about where relational models fail.
  3. Use your fundraise to recruit design partners into the verticals you want to enter next.
    Rather than guessing which vertical to move into after wealth management, Avantos structured their Series A around bringing in strategic design partners in adjacent verticals. The logic was explicit: financial institutions like Guardian Life, Vanguard, and SEI already had established wealth businesses, so starting there and expanding into their adjacent products — life and annuity, brokerage, banking — was a natural motion rather than a cold entry. Each design partner gave Avantos a foothold in a new vertical while de-risking it through a paying, co-building relationship. Founders planning vertical expansion should ask whether their next fundraise can do this work.
  4. When the category label is taken, own the problem frame instead.
    Avantos can't call itself a CRM — Salesforce captured that term and turned it into a sales tool, making it actively misleading for what Avantos does. But rather than spending cycles on category naming, Bassam leads with the pain: client onboarding and servicing in financial services is broken, and buyers recognize it immediately without needing a label. "We show up and we say we focus on client management, particularly onboarding and servicing. Our clients immediately get it." In a market with acute, widely-recognized pain, sharp problem framing produces faster sales cycles than category creation.
  5. For enterprise GTM at the infrastructure layer, your network is your distribution.
    Avantos reached anchor logos — Mercer Advisors, Guardian Life, Vanguard, SEI — without a marketing function. Bassam's framing is precise: selling a foundational platform into large enterprises requires deep client knowledge and credibility, not demand generation. "Going to enterprise and asking to be a foundational layer does not require marketing. It requires you to know the client super well. It requires a network." The implication is also specific: this holds until you need to scale beyond the population your network can reach, which is the forcing function Avantos is now hitting as they expand markets post-Series A.
  6. Lead with the operational metric, not the AI narrative.
    Avantos's buyers have two concerns: data security and job displacement. Bassam addresses both, but the one that actually drives decisions is productivity. In wealth management, there aren't enough advisors to service the clients firms want to reach — Avantos increases advisor-to-client ratio by approximately 30% by their own measurement. That metric translates directly into incremental revenue capacity for the firm, not efficiency savings. When selling AI into conservative enterprise buyers, the question to answer is not "what does the AI do" but "how many more clients can my advisor serve."

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