Meridian, an agentic artificial intelligence startup trying to reinvent complex financial modeling, has the money it needs to complete that mission after raising $17 million in seed funding today.

The round, led by Andreessen Horowitz and The General Partnership, brings the company’s post-money valuation to $100 million.

The startup, officially known as Longitude Labs Inc., is trying to tackle one of the most promising yet challenging use cases for AI agent automation. Financial modeling is an extremely complex business that’s almost always done in Excel spreadsheets, which is why most early efforts have focused on trying to integrate AI agents into Microsoft Corp.’s iconic software. But Meridian believes that’s the wrong approach, as it places major limitations on the functions of AI agents and hinders the ability to audit their work.

Instead of creating an AI agent and letting it loose in Excel, Meridian operates as a standalone integrated development environment. This architectural choice means it can offer more comprehensive functionality than agentic add-ons. For instance, it can integrate diverse datasets and external references, which would be difficult to implement in Excel workflows.

In an interview with TechCrunch, Meridian co-founder and Chief Executive John Ling said financial institutions are heavily regulated and must adhere to very strict rules when building financial models. There’s a need for extreme, verifiable accuracy and consistency, but this clashes with the nondeterministic nature of large language models, he said.

“If you go to 10 different software engineers at Google, and you want to add some new feature into an app, you’ll probably get like 10 completely different implementations,” he said. “But if you go to 10 banking analysts at Goldman Sachs and ask for 10 valuation models for a company, you would probably get 10 almost identical workbooks.”

That underscores the need for standard, reproducible outputs in financial models, and that’s precisely what Meridian is trying to achieve. Its platform blends agentic AI with conventional financial tools and leans heavily on verifiable data to minimize the hallucinations that frequently occur in AI outputs. That allows it to generate deterministic outputs that are consistent and reproducible, Ling explained. Further, its platform provides visibility into every assumption and the logic flow of financial models, in order to facilitate regulatory audits.

“Our goal is to really remove the doubt layer right from the LLM process,” Ling explained. “You know exactly how the logic flows, and all of these assumptions or whatever that go into the model, you can see exactly where they’re coming from.”

That’s exactly what financial institutions need if they’re going to be able to embrace automation and reduce the load on their expensive and overworked human analysts, Ling said. Proof of that comes from Meridian’s early traction. According to the CEO, the startup secured $5 million in contracts in December with clients including Decagon AI Inc. and OffDeal Inc.

With today’s funding, Meridian hopes to accelerate the development of its financial modeling platform and grow its adoption among enterprises seeking faster, more reliable ways to build complex financial models.

Image: SiliconANGLE/Microsoft Designer