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Not Just Another AI Tool: How Mesh Is Solving Real Problems for Accounting Teams
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Global Banking and Finance Review
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From marketing to medicine, industries across the world are racing to capitalize on the potential of artificial intelligence. But in finance, a sector governed by accuracy, compliance, and auditability, adoption has been far slower and cautious.
From marketing to medicine, industries across the world are racing to capitalize on the potential of artificial intelligence. But in finance, a sector governed by accuracy, compliance, and auditability, adoption has been far slower and cautious.
Historically, financial organizations of all shapes and sizes have faced significant barriers to digitization and automation because they are high-stakes and incredibly complex. Mistakes can cost millions in direct losses and compliance or audit failures.
Software engineer and AI expert Nandini Ramakrishnan is creating the next generation of AI-powered financial tools at Y Combinator-backed startup, Mesh.
With over a decade of experience applying new technological developments to fintech applications, she’s using her analytical knowledge of financial infrastructure to create AI agents that can handle reconciliation, audit prep, and ledger categorization.
Here’s a closer look at Nandini’s career, design philosophy, and groundbreaking work at Mesh.
After graduating from Carnegie Mellon University with a master’s in electrical and computer engineering, Nandini joined eBay’s new product development team, where she helped reengineer the company’s global shopping experience for the Chinese market.
But it was at Carta where she really came into her own. She rose from engineer to technical lead and then engineering manager in just four years, helping grow the business to over $100M in annual revenue.
She worked on vital systems like the audit portal and fund formations engine, which had to withstand scrutiny from auditors, internal stakeholders, and enterprise clients. At the same time, she won multiple Carta hackathons, continually increasing her technical expertise and skills to meet the emerging marketplace.
Today, Nandini is the CTO and co-founder of Mesh, a platform which builds trustworthy AI agents that can overcome the conventional barriers between complex financial tasks and AI automation. Financial workflows need more than flashy AI that promises productivity, they need powerful, robust tools that comply with rigorous compliance standards and work effectively without human intervention.
Mesh is a full-stack solution that can handle highly manual and individualized systems to fully manage error-prone and messy processes, including:
Financial teams can treat Mesh AI agents as full partners that bridge the gap between their in-house business data and their accounting system.Mesh provides a wide selection of different building blocks which teams can choose, deploy, and train on organization-specific processes, significantly reducing the time spent on processes and eliminating delays and bottlenecks around the monthly close.
Instead of AI being a supplemental feature, it becomes the infrastructure that completes the accounting work.
For Nandini, the hardest and most important part of building Mesh has been ensuring that its outputs can be trusted. This means designing systems that are explainable, which is why Mesh’s AI agents are built with control layers, audit logs, and override mechanisms. They’re not black boxes, they’re collaborators.
These principles are part of her new design philosophy, which involves making AI agents structured, secure, and capable of integration with ERP software. This is a real breath of fresh air for organizations that have hesitated to add AI adoption to their roadmap because of security and compliance concerns..
In a market full of flashy prototypes and GPT wrappers, Nandini’s seriousness about design is what sets Mesh apart.
Nandini Ramakrishnan didn’t start Mesh as a demo project or a fundraising tool. She started it because she saw how broken financial workflows still are up close and knew what it would take to fix them. Her bold long-term vision is a world where intelligent agents handle the boring, repetitive work so human teams are free to focus on strategy, analysis, and decision-making.
Mesh is already being used by startups and finance teams who want robust tools that can operate across legacy software and systems seamlessly and without making silly errors.
For Nandini, the goal isn’t just innovation, it’s dependability. And in fintech, that may be the most disruptive thing of all.
Artificial intelligence (AI) refers to the simulation of human intelligence in machines programmed to think and learn like humans, enabling them to perform tasks such as problem-solving and decision-making.
Compliance in finance involves adhering to laws, regulations, and guidelines set by governing bodies to ensure that financial institutions operate within legal frameworks and maintain ethical standards.
Financial technology, or fintech, refers to the integration of technology into offerings by financial services companies to improve their use of financial services, making them more efficient and accessible.
Reconciliation in accounting is the process of ensuring that two sets of records (usually the balances of two accounts) are in agreement, helping to identify discrepancies and maintain accurate financial records.
Audit preparation involves organizing financial records and documentation to ensure compliance with accounting standards and regulations, making the audit process smoother and more efficient.
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