Sunny Ray talks with Shikha Miglani, co-founder of Saarthee and founder of Maithee, about her move from running a boutique data and analytics consultancy to building AI products. Shikha explains the Sanskrit meaning of Saarthee, a guide or companion, and how the firm pairs subject matter experts with small, skilled teams to connect data quality with business strategy. She describes growing through word of mouth for roughly the first eight years before investing in a sales team, and how conversations with prospects revealed demand for an end-to-end platform rather than a patchwork of vendors. Shikha shares how her team reacted when she chose to build products that cannibalize their own services, why product growth is non-linear while services growth is linear, and what excites her most about her analytics platform. She also outlines her goals for the year, which center on quality customer engagements over volume, and describes the two types of enterprise buyers she meets. The conversation closes with how to connect with her.
Shikha Miglani explains why she chose to cannibalize her own consulting firm by building AI products, and why quality beats volume.
What does the name Saarthee mean, and how does it shape the way you work?
Saarthee is a Sanskrit word meaning mental guide or companion, drawn from the Mahabharata, where one brother chose a guide over a million soldiers. The lesson is that quality beats quantity. Every team has a subject matter expert leading a small, elite group, so we can do the groundwork on data, drive the technology, and still speak the language of the business.
What problems did you see big companies failing to solve with their own data?
There were two. First, the data was not reliable, so nobody trusted it. Second, nothing brought it all together into strategy. We built proprietary tools to improve data quality, then married business, technology and data to deliver actionable insights. Strategy meant focusing on the why and on what a CMO or vice president needs to succeed in their annual roadmap.
How did your first enterprise clients find you, since you did not build a sales team for years?
It was word of mouth. Founder-driven companies bring energy and freshness, and you are personally invested in the work. Many stakeholders were friends, and we wanted to make them look good. For about the first eight years we just did the work. Once our recipe was in place, we slowly moved into a sales process, and then AI arrived.
When did you realize you could turn your team's learnings into a product?
It did not happen on day one. On sales calls I kept hearing problems about how to use AI, and DIY AI was not helping enough. I asked why we should not transfer our learnings onto one platform, so enterprises avoid juggling vendors. I started with two or three modules, and now there are six or seven.
What was it like telling your team you would build products that compete with their own services?
It was very natural. My team knows I am authentic and open to new experiences. A company like ours should focus on creating long-term value rather than holding on to revenue. People are not limited by their roles here. If someone is in analytics, I welcome them into product modules, and the team got excited about pushing boundaries.
How did your thinking about growth change once you were selling software instead of hours?
Growth becomes non-linear. In services it is linear, with more people meaning more revenue. With AI products, we can reach the same revenue with far fewer people. Some products will still need specialized human and domain expertise, like forward deployed analysts, but the product side scales very differently from the services side.
Which product are you most excited about right now?
It is our own analytics platform, where I cannibalize myself. It serves the whole analytics value chain, led by humans and assisted by AI, and delivers reliable insights rather than just processing data. I knew it would shrink my own team, which is fine. Analytics is about hitting the goal, which means insights you can rely on.
What has to be true by year end for you to call it a win?
We are already winning, and I started out building something I am passionate about. This year I am not chasing volume. I want quality engagements with AI-first organizations so I can sharpen the products and innovate quickly with customers. Investment is something I will consider, probably next year, but I am in no hurry.
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