Revolutionizing Enterprise Back-Office Operations: Ananth Manivannan's Resolvd AI Brings Cognitive Execution to the Forefront
In an exclusive interview,Resolvd AI founder Ananth Manivannan reveals how his cognitive execution system is revolutionizing enterprise back-offices & reshaping the future of AI in business operations
Ananth Manivannan, the visionary founder of Resolvd AI, is on a mission to revolutionize enterprise back-office operations through innovative AI technology. With a background in Industrial Engineering and software development at industry giants like PepsiCo and Capital One, Manivannan has uniquely positioned himself to address the inefficiencies plaguing modern businesses.
In an exclusive interview with AI World Today, Manivannan shares insights into Resolvd AI's revolutionary Cognitive Execution System, which deploys AI agents as digital team members for enterprise back-office teams. These agents go beyond mere analysis, autonomously solving complex problems by managing the intricate "swivel chair" work that exists between various company systems. From handling email requests to navigating multiple databases, Resolvd AI is redefining how businesses approach data reconciliation and operational efficiency.
With a recent $1.6 million pre-seed funding round under their belt and major US health systems already on board, Resolvd AI is poised to make a significant impact in the healthcare industry and beyond. Manivannan's vision extends far beyond simple automation, aiming to create a comprehensive AI-driven operating system for enterprise back-offices that will transform how businesses handle complex, judgment-heavy work in the digital age.
Can you introduce yourself and give us a brief overview of Resolvd AI?
My name is Ananth Manivannan, and I'm the founder of Resolvd AI. We're building what we call a Cognitive Execution System. In simple terms, we build AI agents that act as digital team members for enterprise back-office teams. Our agents don't just analyze problems, they autonomously solve them by handling the messy, manual "swivel chair" work that exists between a company's systems, like emails, spreadsheets, and their core ERP.
For example, when a request comes in to add a new SKU to the item master database via email, an analyst would have to check the contracting system to find the corresponding contract; check if the SKU is under contract; verify the SKU price and values; check the ERP to ensure it hasn’t been added before; examine similar SKUs to validate naming convention for the addition; fill in a VBA enabled Excel template to add the SKU; and finally check the ERP to ensure it was added correctly. This is the classic swivel chair workflow of swiveling between multiple data sources to execute a task. It’s a cumbersome, time-consuming, error-prone process.
What inspired you to start Resolvd AI, and how does your previous experience at PepsiCo and Capital One contribute to your current role?
The idea for Resolvd came from living the problem from two different sides. As an Industrial Engineering grad working in supply chain at PepsiCo, I was the person doing the manual swivel-chair work. I was responsible for master data, and I spent my days reconciling data between spreadsheets, supplier portals, and our SAP system. It was incredibly inefficient.
Later, as a software engineer at Capital One building cloud automation tools, I was on the other side, building the powerful, structured systems. I saw the huge gap that still existed between these elegant systems and the messy, unstructured way the business actually operated. I realized the biggest opportunity wasn't to build another ERP, but to build the intelligent bridge between the two worlds. That unique combination of deep operational knowledge and enterprise-grade software experience is the foundation of Resolvd.
Congratulations on your recent $1.6 million pre-seed funding round. How do you plan to utilize these funds to scale your business?
Thank you. The funding is an accelerant for a very focused plan, which will accomplish three things. First, we’ll deepen our integrations in our beachhead market, which is the US hospital back-office. This means building out our proprietary library of 'human-way' integrations for legacy systems like Epic and PeopleSoft. Second, we’ll scale our delivery to flawlessly execute for our foundational health system customers who are trusting us with major innovation efforts. Finally, we’ll hire a small, elite team of founding engineers who are passionate about solving these complex, real-world problems.
Could you explain in simple terms how Resolvd AI's technology works to automate complex reconciliation workflows?
Imagine an invoice gets stuck because the supplier name doesn't perfectly match the Purchase Order. Today, a human has to see that error, open three different systems, hunt for the right information, and manually fix it.
Our AI agent does the same thing, but it does so autonomously. It monitors the queue, understands the context of the error - 'Stryker North America’ is the same as 'Stryker USA' - searches the other systems to confirm the correct data, and prepares a validated, clean transaction for a human's final approval. We're essentially automating the cognitive 'detective work' that humans are currently forced to do.
You mentioned that Resolvd AI has already signed major health systems in the US. What specific challenges in the healthcare industry does your solution address?
We are already deploying our workers at leading health systems to tackle multi-million dollar problems like stopping the revenue leakage that occurs when non-catalog, high-cost surgical items aren't properly billed; intricate match exceptions that I mentioned earlier; item master maintenance; access provisioning and more.
How does Resolvd AI's approach differ from traditional methods of handling operational requests and data reconciliation?
The traditional approach has been a choice between two flawed options: hire more people, which is expensive and doesn't scale; or try to use brittle technologies like RPA, which are designed for simple, repetitive clicks and break when they encounter any complexity or judgment.
Our approach is different. We're not automating clicks; we're automating cognitive work. Our agents can handle unstructured data, make deductive inferences, and navigate systems the way a human would. This allows us to solve a class of complex 'swivel chair' problems that traditional automation has never been able to touch.
Can you share an example of how Resolvd AI has helped a client improve their operational efficiency?
At one of our health system partners, the process of adding a single new item to their master data system took days and involved an average of seven to ten back-and-forth emails to get the right information. By deploying our agent to manage this intake and reconciliation process, we are on track to reduce that cycle time by over 90 percent. This will up their highly skilled supply chain team and enable them to focus on strategic sourcing instead of manual data entry.
What are the primary industries or sectors that can benefit most from Resolvd AI's solution?
Our beachhead market is unequivocally the US hospital back-office. It's a perfect fit: high stakes, massive amounts of unstructured data, legacy systems and a reliance on expensive manual labor. However, the core 'swivel chair' pattern exists everywhere. We see a clear path to expand from healthcare into other legacy-system-heavy industries like manufacturing, logistics and financial services operations.
How does artificial intelligence play a role in your platform, and what advancements in AI technology are you most excited about?
AI is the core of our system. We use large language models for understanding the intent behind unstructured requests; computer vision for reading documents and PDFs; and a multi-agent framework that allows our system to reason, plan and execute complex tasks.
I'm most excited about the advancements in agentic systems and multi-modality. The ability for an AI to not just understand text, but to also see a screen, interpret an image of a product, and use tools like a human would is the technological leap that allows us to move beyond simple chatbots and build a true cognitive execution system.
With the increasing concern about data privacy and security, how does Resolvd AI ensure the protection of sensitive information during the reconciliation process?
This is paramount for us, especially in healthcare, and we use a multi-layered approach. First, we use best-in-class, HIPAA-compliant infrastructure through providers like AWS GovCloud. Second, our agents are designed to work with the minimum amount of data necessary to perform a task. Finally, we offer flexible deployment models, including the ability for a client to host the system within their own environment to ensure that their sensitive data never leaves their control. Security and privacy are foundational to our architecture, not an afterthought.
What do you see as the biggest challenges in scaling a startup in the AI and automation space?
The biggest challenge is moving beyond the 'cool demo' and delivering real, tangible ROI in a complex enterprise environment. Many AI tools are impressive, but they fail when they hit the messy reality of a customer's legacy systems and unique business processes. Another challenge is the 'last mile' problem; it's one thing to identify a problem, but it's another to reliably and safely execute a solution inside a customer's critical system of record. Overcoming these integration and execution hurdles is what separates lasting companies from short-lived hype.
How do you envision Resolvd AI evolving in the next 3-5 years?
In 3-5 years, I envision Resolvd as the indispensable operating system for the hospital back-office. We will have a comprehensive suite of AI agents that manages the entire lifecycle of supply chain, procurement and financial operations. Rather than thinking of us as a tool, our customers will see us as a core part of their digital workforce. From that dominant position in the healthcare space, we will expand our platform into our second and third major verticals, proving that our model for automating complex, judgment-heavy work is a universal solution for the modern enterprise.
What advice would you give to aspiring entrepreneurs who are looking to start a company in the AI or enterprise software space?
Don't over complicate the solution. Don’t overthink the competition. Everything seems so saturated right now and feels like the tail years of the dot com era when everyone thought “all the good ideas are taken.” The truth is, we are early, no one has separated themselves in any of these domains, market capture is sub .1% in almost all application layer industries, and 95% of the companies that exist today won’t be here in five years. So just start, find a problem you know you can solve and that someone will pay you for. If venture capital is the route you want to go, don’t pitch what you are building today; no one cares. Pitch what the grand unbelievable outcome will be in 10 years if everything works in your favor. That’s your venture backable story, and far too often, founders over-index on where they are today. That humility is great in life, but not in startups.
Lastly, how can our readers learn more about Resolvd AI or get in touch if they're interested in your solution?
Visit our website resolvd.ai and for more frequent updates, connect with me on LinkedIn!
Ananth Manivannan's Resolvd AI represents a paradigm shift in enterprise back-office operations. By leveraging advanced AI technology to bridge the gap between legacy systems and modern automation needs, Resolvd AI is tackling some of the most persistent challenges in data reconciliation and workflow management. As the company continues to evolve and expand its reach beyond healthcare into other industries, it's clear that Manivannan's innovative approach to cognitive execution systems will play a crucial role in shaping the future of enterprise operations. With its focus on delivering tangible ROI and overcoming complex integration hurdles, Resolvd AI is well-positioned to become a leader in the next generation of AI-driven business solutions.