AI accounting apps have grown exponentially in recent years, with the compound market size rising from $4.74 billion to $6.98 billion between 2024 and 2025 alone. However, this incredible growth has come with some steep challenges, especially when it comes to AI system design.
While other AI architects approach AI applications as add-ons to existing systems, software engineer Nandini Ramakrishnan has reimagined how AI agents can be structured from the ground up, setting new standards for safety, controllability, and usability in the world of accounting software along the way.
Nandini is now the CTO of AI finance platform, Mesh, where she's channeling a decade of engineering and financial automation experience into building intelligent systems that can safely and reliably perform complex accounting tasks.
Here's a closer look at her early life, career, and groundbreaking work at Mesh.
Ramakrishnan Brings an Engineer's Approach to Cognitive Systems
From her early start with coding at the age of eight to earning both bachelor's and master's degrees in electrical and computer engineering from Carnegie Mellon, Nandini has demonstrated a tendency to veer away from abstractions and work in hard realities instead.
She credits this mindset to her grandmother, an accomplished mathematician who tutored her after school and became her earliest mentor in the STEM field: "Thanks to her, it always felt ingrained in me to look at everything from an analytical perspective," says Nandini. With that mindset ingrained in her early on, her move to engineering felt almost inevitable.
After graduating, Nandini's interest in analysis and engineering stood her in good stead as she moved into various tech roles. She worked on eBay's New Product Development team to revamp the online shopping experience for the Chinese market, and later as a software engineer at equity management platform Carta, where she helped scale the company's ARR from $20 million to over $100 million.
Nandini's work in finance and accounting AI has been invaluable in an industry where trust runs at a premium and even small errors can have massive consequences.
Ramakrishnan and the Mesh Model
In 2024, Nandini co-founded Mesh, a Y Combinator-backed startup that is building AI agents for accounting workflows.
Most AI agents today are essentially glorified digital assistants that automate repetitive tasks by running on a series of if/then decision trees. These models are helpful to a point, but they are less effective in the complex and error-prone systems found within accounting software.
The Mesh model takes a completely different approach to AI architecture by completely reengineering AI agents and layering their processes from the ground up in ways that allow each agent to serve as its own deterministic micro-system.
Rather than operating on simple if/then trees, Mesh's AI agents ingest custom financial or operational data, map it against logic modules, run validation gates, and expose internal decision paths. They're less tools and more full integrations into accounting software infrastructure.
The beauty of this approach is that no single model makes all the decisions, and the system of layers allows for both redundancy and higher levels of control, both qualities that add layers of safety in the high-stakes world of automated bookkeeping.
Ramakrishnan Designs for Edge Cases, Not Demos
All systems tend toward disorder, including automated ones, which is why the Mesh model is built around the expectation that models will fail. Building for failure first may sound counterintuitive, but this approach has led to AI models built to survive in the real world, not just make a big splash in pitch meetings.
Nandini believes that safe automations are ones that know the system isn't always right, and therefore shouldn't always have the final say independent of human input. To that end, the Mesh model embeds intricate override logic as a failsafe so automated infrastructures are safer and more trustworthy.
Ramakrishnan Isn't Just Building a "Fintech Tool"—She's Building Agent Infrastructure
Financial infrastructure in which AI agents work reliably with minimal human input and oversight is no longer just a pipe dream. Thanks to leaders like Nandini Ramakrishnan, accurate, real-time accounting automation powered by AI is now a reality.
She recently represented Mesh on the Y Combinator Demo Day stage, presenting the company to more than 1,000 investors. She also regularly shares updates on product development at community events: recently with the GenAI Collective, during a Product Hunt showcase, and at a closed-door AI Privacy panel hosted by Founders Creative.
Nandini's voice is invaluable, and her career speaks for itself. She's leading the way for other engineers and product leaders working with AI systems, who can look to her work for a blueprint for building reliable, trust-first AI infrastructure.
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