Cracking the Code: How SOLVE Is Transforming Muniland with AI

Part 1: Cracking the Code: How SOLVE Is Transforming Muniland with AI

Rewriting the Playbook for Munis

The municipal bond market has long been associated with manual processes, limited transparency, and sluggish adoption of technology. But that landscape is evolving rapidly. SOLVE, under the leadership of CEO and co-founder Eugene Grinberg, is at the forefront of this transformation, bringing advanced data science and AI to a space that has traditionally resisted change. On Bloomberg’s Masters of the Muniverse podcast, Eugene walked listeners through SOLVE’s mission, and how his background in structured finance and enterprise tech laid the foundation for a data-centric revolution in fixed income.

A Founder’s Path from CDOs to Transparency

Eugene began his career building models for structured products, getting a firsthand look at the complexity and opacity in the bond markets. It was during these early years that he and co-founder Gerard Nealon noticed just how fragmented the data environment was—across the buy and sell sides. While firms could develop internal models to estimate value, they were flying blind when it came to actual market signals embedded in quotes and messages. SOLVE was born from the idea that by capturing, standardizing, and organizing this flood of conversational quote data, firms could finally make smarter, faster decisions in real time.

Building a Product Around a Real Market Need

In the early years of SOLVE, they spent their time meeting potential clients, gathering feedback, and adapting quickly to it. This direct engagement with market participants revealed a shared pain point across firms: the inability to wrangle tens of thousands of daily quotes into usable, actionable insights. SOLVE’s core platform was designed to address this challenge from day one, aggregating fragmented quotes and turning them into organized, anonymized data streams that benefit both buy-side and sell-side participants. What started as a transparency tool quickly became a critical workflow solution. “We kept hearing the same thing, ‘the market is flooded with quotes and messages, and no one can keep up.’ That’s the gap we knew we had to close.”

From Four Employees to Market Impact

Today, SOLVE has grown to over 170 employees and serves more than 300 clients. That growth has been both organic and accelerated through outside capital. Eugene candidly shared how fundraising itself was a learning journey—forcing him to adopt a new “language” around metrics, product-market fit, and investor expectations. But the infusion of capital allowed SOLVE to scale its engineering team, improve its product suite, and expand into new asset classes. What hasn’t changed is the company’s obsession with listening to customer pain points and solving them with real-world, usable technology.

Standing Out in a Crowded, AI-Driven Field

As artificial intelligence becomes more accessible, the market has seen an influx of new pricing vendors. However, Eugene pointed out a critical difference: while many players rely on public trade data and reference terms, with the power of the flagship SOLVE Quotes product, the company’s edge lies in its ability to extract meaning from highly conversational quote messages, millions of them daily. That quote data is difficult to access and even harder to clean, but it’s where true price discovery lives. This proprietary data gives SOLVE a significant advantage, ensuring that its predictive tools are both unique and grounded in real-time market signals. Additionally SOLVE continues to expand its suite of relative value analytics and visualization tools to help its clients build conviction in their pricing and idea generation. In Part 2, we’ll dive deeper into how SOLVE’s predictive models actually work, why they outshine traditional pricing services, and what the future of Muniland might look like when AI takes the wheel. Check out the podcast to learn more about how SOLVE is bringing sharper data, better tools, and real-time intelligence to fixed income.

Where to listen: Apple  | Bloomberg | Spotify