Agilow

Carnegie Mellon University, Tepper School of Business

Industry: Software & SaaS

MBA Founding Student Name(s): Shiv Panjwani

Brief Description of Solution: Agilow reduces meeting and messaging overload for software development teams by creating conversational, voice-AI teammates who can literally call you, talk to you on the phone, and carry information across the team. These AI teammates listen to standups, planning meetings, and bug discussions, and instantly translate those conversations into clean documentation. They update kanban boards, surface blockers, and keep everyone aligned without the constant need for synchronous meetings.

Funding Dollars: $35,000

What led you to launch this venture? Prior to beginning my MBA, I used to run an Agile consulting firm. Through this, I experienced the transformational difference effective collaboration techniques can make to employee lives, office culture, and business productivity. I noticed that a big bottleneck in effective collaboration was effective documentation of meeting outcomes – updating kanban tickets, updating goals during times of change, and maintaining retrospective journals. We hypothesized that voice-AI agents maintaining documentation would improve a professional team’s ability to more consistently stick to the processes and meeting rituals they set for themselves.

What has been your biggest accomplishment so far with venture? We successfully helped a Carnegie Mellon based startup get acquired – helping both founders achieve the outcomes they desired. It was quite empowering for us to help a group of passionate people achieve a tough goal. We helped the founders document their acquisition goals six months prior to acquisition, and used our software to help them plan, execute, and reflect weekly on their progress. Through the process of continuous improvement and planning, facilitated by Agilow, we were able to help them reach their acquisition targets on time.

What has been the most significant challenge you’ve faced in creating your company and how did you solve it? The biggest challenge was shifting from being an Agile consultant to becoming the CEO of an AI SaaS company. Recruiting strong technical talent was especially tough. CMU has some of the best engineers in the world, and they want to work with founders who can speak the language, understand product depth, and make real technical decisions.

To solve this, I rebuilt my technical foundations from scratch. I took AI-driven classes, joined hackathons, and immersed myself in Pittsburgh’s AI community. I focused on learning modern tools, understanding the architecture behind our product, and showing engineers that I was willing to do the work. That effort helped me attract the right talent and build the level of credibility needed to lead a technical company.

How has your MBA program helped you further this startup venture? The full-time MBA has been the most powerful accelerator for my startup journey. A lot of people love saying that the MBA is a waste of time. I strongly disagree. If you approach it the right way, the MBA is a two-year incubator where you get to build a company with professors, experts, and resources that you could never access on your own. That is especially true at Carnegie Mellon.

The program helped me understand the kind of leader I want to be, what drives me, and what I stand for. That level of self-awareness builds confidence, which is the most valuable currency for any entrepreneur.

On a tactical level, the Tepper School MBA gives you an unfair advantage. The first year gives you the strongest possible foundation in accounting, finance, organizational behavior, and decision optimization. These classes teach you how to think about your business beyond just the product.

The entrepreneurship track at the Tepper School is tightly connected with the Swartz Center for Entrepreneurship. You get access to mentors, investors, founders, and hands-on courses in Business Model Canvas, Human Centered Design, Lean Agile thinking, co-founder equity, and early-stage fundraising. The worst case is you graduate with elite skills and an extraordinary network. The best case is you build your company while you are here.

Which MBA class has been most valuable in building your startup and what was the biggest lesson you gained from it? The most valuable class for my startup has been the AI Venture Studio taught by Sean Ammirati and Adam Paulisick in the School of Computer Science. The entire class is built on one idea: learn how to use AI to 100x yourself as a founder. You go through customer discovery, design thinking, rapid prototyping, and investor storytelling, and you do all of it with AI tools at your side.

Agilow was born in that class. Our first customers and our first investors came directly from the work we did there.

My biggest lesson was simple. If I want to be the CEO of a tech company, I have to be comfortable building with technology and understanding the product at a deeper level. I also learned how important it is to communicate technical work in a way that a non-technical audience can understand. That combination has been critical to our progress ever since.

What professor made a significant contribution to your plans and why? Adam Paulisick made a significant impact on my plans. He gave me tough feedback exactly when I needed it. He told me that my audience was too broad and pushed me to narrow my focus to a specific user with a specific pain point. That shift changed the entire direction of our product.

He also encouraged me to reconnect with my roots as an engineer, something I had stepped away from while consulting. He pushed me to build, experiment, and get hands-on with the technology again. On top of that, he introduced me to mentors and investors and guided me through team dynamics, equity splits, and early-stage capital formation.

At CMU, every entrepreneur finds their own version of Adam. They are people who believe in you, challenge you, and help you grow. I feel incredibly grateful to be part of a community like that.

How has your local startup ecosystem contributed to your venture’s development and success?
Pittsburgh is the biggest small city. You get all the technology, research, and depth of a major hub, but the entrepreneurial community is tight, supportive, and genuinely connected.

This ecosystem directly shaped Agilow. I found my co-founder by putting a flyer in the Swartz Weekly Bulletin. When I was stuck on my first product demo, a founder friend at Swartz sat with me and helped me get through the technical issues. Innovation Scholar and Swartz EIR, Matt Spettel, introduced me to our first investor. Moments like this kept the company moving when it mattered most.

The broader Pittsburgh startup ecosystem has been just as important. Communities like CMU T&E, AI@Work, PDMA, and InnovatePGH opened doors to advisors, customers, mentors, and champions. The Swartz Center even gave our team garage space, which became our first real office. Having a place where we can host investors, customers, and potential hires without worrying about rent has been a huge advantage.

Pittsburgh is the home of Robotics and AI. When you build an AI company at Carnegie Mellon, you get a natural boost from being embedded in one of the most innovative environments in the world.

What is your long-term goal with your startup? Our long-term goal is to bring human AI collaboration into blue-collar and manufacturing environments, where adoption is usually the hardest, but the impact is the highest. We believe the future workplace will include AI teammates who transfer information across departments, update systems in real time, and keep teams aligned without adding extra meetings. We already see early versions of this in customer service and asynchronous interviews, and that shift is only accelerating. Agilow aims to build the technology that bridges this gap and makes AI adoption simple, practical, and culture improving for frontline and industrial teams.

Looking back, what is the biggest lesson you wished you’d known before launching and scaling your venture? The biggest lesson I wish I had learned earlier is how to ask great customer questions. I thought I was doing interviews, but I was instead biasing people without realizing it. Books like The Mom Test and design thinking training helped me empathize better, understand the exact situations where users feel pain, and focus on specific problems rather than broad assumptions. Stronger discovery skills would have helped me build clearer products and communicate our value much earlier.

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