From Oracle to Building Two Startups: Shyam Panda's Journey with DiLytics & Slash

What do you do when you have a consumer marketplace idea but lack the technical skills and funding to build it? For Shyam Panda, the answer was brilliant in its simplicity: build a different company first. Armed with deep Oracle expertise, he founded DiLytics in 2011, grew it into a successful analytics consultancy serving mid-market customers, and then used those revenues to fund his real passion project—Slash, a home services marketplace featuring dynamic pricing.

Nine years later, this strategic approach has created two thriving companies: DiLytics with 92 employees specializing in Oracle analytics solutions, and Slash, which is revolutionizing home services in Hyderabad with AI-driven pricing that can offer the same haircut for ₹200 on a Monday morning or ₹500 on a weekend.

From a small town in Odisha to Silicon Valley's Oracle headquarters to building two companies simultaneously, Panda's journey reveals the power of strategic patience and leveraging existing expertise to fund future dreams.

From Small Town Odisha to Silicon Valley Excellence

Shyam Panda's entrepreneurial journey began in the most unlikely place: Sambalpur, a small town in Odisha where entrepreneurship wasn't part of the cultural DNA. "I was born in a small town in the state of Odisha, a small town called Sambalpur," he recalls, before his family moved to the capital city of Bhubaneswar for his formative education years.

His educational path followed a classic Indian engineering trajectory: state board public schools through 12th grade, then NIT Rourkela for engineering, followed by an MBA from Xavier's Institute of Management, Bhubaneswar. But it was his five-year stint in Bangalore's software industry that first exposed him to entrepreneurial possibilities.

The Oracle Catalyst: Learning from the Inside

The pivotal moment came when Panda moved to the United States to join Oracle Corporation as a product manager for their data analytics products. For four years at Oracle's headquarters, he gained invaluable insights into both the potential and limitations of enterprise software implementations.

"As a product manager for Oracle's data analytics product, we worked with many different stakeholders—from product development to product support to product sales to product implementation by Oracle partners," Panda explains. "I noticed time and time again that it wasn't easy for all Oracle partners to implement the Oracle data analytics product for customers."

This observation became the foundation for his entrepreneurial confidence: "While there were many successful implementations, there were also many failed implementations. Being a product manager for the data analytics product, I knew the product inside and out. I thought I could ensure that the customers we take up will have successful implementations."

Silicon Valley's Entrepreneurial Magnetism

Beyond technical insights, Silicon Valley provided the cultural catalyst that transformed ambition into action. "Entrepreneurship is something that I didn't think about overnight. It has been an ambition for a long time, especially after I started working in the software industry," Panda reflects.

The Valley's influence was exponential: "After I moved to the US and worked for Oracle Corporation for four years, being in Silicon Valley, the inspiration was all the more exponentially high, which drove me to take the risk of leaving the comfort zone of having a job and start my first venture."

The psychological shift of international relocation also played a crucial role: "When you move internationally from one end of the world to the other, you pretty much start a new life. You feel like you have nothing to lose because you're starting fresh anyway."

Building DiLytics: The Strategic Foundation (2011-2020)

In 2011, armed with deep Oracle expertise and Silicon Valley inspiration, Panda launched DiLytics as a systems integration and solution partner focused entirely on analytics, data intelligence, data warehousing, ETL data integration, and enterprise performance management solutions.

The Target Market Strategy

Rather than competing directly with Oracle's massive enterprise implementations, Panda identified a strategic niche: mid-market Oracle customers who couldn't afford the big players in the systems integration space.

"Having come out of the Oracle ecosystem, I had great relationships within the Oracle sales team, pre-sales team, product development team, and product support team," he explains. "Oracle works with large enterprises, but they also work with mid-sized customers. Our target market was the mid-market Oracle customers."

To build deeper expertise, DiLytics focused on specific verticals: pharma, life sciences, and manufacturing—industries with complex data requirements but limited resources for premium consulting services.

Building the Team: Network-First Hiring

As projects multiplied, Panda faced the classic scaling challenge of technical services businesses. His approach to hiring offers valuable lessons for first-time entrepreneurs:

Start with Your Network: "One of the things that many entrepreneurs do is hire people from their network—people they already have worked with in the past. The first few people I chose were either people I knew I had worked with or people that my contacts knew."

Leverage Trusted Recommendations: "My contacts had worked with them and had given me the thumbs up that these are some great people you would love to work with."

Scale Through Systems: "Not every hire can come through contacts. After that, you have to streamline your recruiting process to hire from the market as well."

The Offshore Advantage

Recognizing that offshore delivery wasn't a competitive advantage but rather "table stakes" in the systems integration space, Panda established operations in Hyderabad through a local partner.

"If any company wants to survive and compete in the system integration space, then one has to have some level of offshore component in their business," he emphasizes. "Me coming from India, obviously we already know about the Indian landscape—technology landscape, cultural landscape, geographical landscape."

This strategic decision enabled DiLytics to compete on cost while maintaining quality, eventually growing to 92 employees and establishing itself as a respected Oracle analytics partner.

The Technology Evolution: From On-Premise to AI

Over DiLytics' nine-year journey from 2011 to 2020, Panda witnessed and navigated three major technological shifts that fundamentally changed the data analytics landscape.

Wave 1: The Cloud Migration (2015-2016)

"When we started, everything was on-premise—customers' own data centers, their own servers, which is where data analytics software used to reside," Panda recalls. "But pretty soon, maybe after four or five years, cloud started making ground in the data analytics space."

DiLytics positioned itself ahead of the curve: "We were one of the first few within the data analytics ecosystem that started doing cloud analytics deployment projects, both in the commercial private sector space as well as in the public sector space."

This early cloud adoption expanded their market beyond private pharma and manufacturing clients to include public sector agencies equally keen to leverage cloud capabilities.

Wave 2: The AI Revolution (2022-Present)

The emergence of ChatGPT and widespread AI adoption has created what Panda calls a fundamental shift in how analytics works:

Traditional Analytics: "Everything that we do in analytics used to require development for every question that business users have. Either they already have a dashboard, or they have to build new dashboards for any new questions—which is time-taking, effort-intensive, and by the time they get insights, it's too late for them to make decisions."

AI-Driven Analytics: "With AI-driven analytics, all they have to do is ask questions as if they are asking a data scientist. AI can answer those questions in real time. You don't have the cost involved with a data scientist, you don't have the time involved to get answers to your questions."

The Impact on Data Science Jobs

Panda provides a nuanced perspective on AI's impact on data science roles, avoiding both extreme doom and unrealistic optimism:

Immediate Impact (60-70% reduction): "Just like every other space where AI is getting relevant, even if it's not eliminating jobs 100%, it is reducing the amount of work that needs to be done by human beings by 60-70%. If we needed 10 data scientists for 100-200 business users, now we will need three or four instead of 10."

Infrastructure Still Required: "AI still needs to be provided with data pipelines—the data infrastructure. That technical work does not go away, at least not in the immediate future."

Future Uncertainty: "At some point when AI is mature enough that it does not have any hallucination issues, then probably that's a theoretical question as to when that is going to happen."

The Cloud vs. On-Premise Debate: A Settled Question

Having navigated both on-premise and cloud implementations across various industries including banking, Panda offers a definitive perspective on a debate that many organizations still grapple with.

Why Cloud Always Wins

"To me, the debate about cloud versus on-premise is a dead debate. Cloud is the only way to go forward," Panda states emphatically.

His reasoning centers on expertise rather than cost:

Specialized Expertise: "Cloud is similar to outsourcing. Sometimes outsourcing may not be cost-effective, but it's about getting the absolute best expertise or skill that a team or company has, which is better than any one company can have."

Economies of Scale in Security: "If a company is only taking care of data center business for hundreds or thousands of customers, then they can do the job of data center management 100 times or 1000 times better than any one company."

Counter-Intuitive Security Argument: "By being on-premise, a company's data is no more secure. In fact, it's rather at risk because they're only managing their own data, whereas cloud companies manage hundreds or thousands of companies' data—that's something they have built expertise on for years."

The Scaling Imperative

Beyond security, Panda emphasizes the operational advantages: "If you are running your own data center, your own servers, then for every scaling that you need to do, you need to be buying, procuring servers, and managing them—which is not your core strength. Your non-core strength should be outsourced just like many things get outsourced to other companies that only do that."

Slash: The Consumer Dream Funded by B2B Success

While DiLytics was growing into a successful Oracle analytics consultancy, Panda was methodically working toward his original entrepreneurial vision: a consumer marketplace that would solve a personal pain point he'd experienced repeatedly.

The Original Inspiration

"Slash is something that I had aspired for even before I started DiLytics in 2011. In fact, I started DiLytics just so that I would be able to pursue the idea of Slash at some point when I had generated enough funding through DiLytics to launch the initial product development for Slash," Panda reveals.

The problem was deeply personal: "The idea for Slash came initially through the difficulty of finding somebody to do household work—when it comes to plumbing or house cleaning—exactly at the time that we need that work to be done."

The process was frustratingly inefficient: "It involved online search, making multiple phone calls, looking at my calendar to finally zero in on that one service professional who will be able to provide the service at the time when I need it. It was at least an hour's job to finally zero in on the service provider, if not multiple hours."

The Strategic Wait

Rather than pursuing Slash immediately, Panda made a strategic decision that many entrepreneurs overlook: play to your strengths first, then use that success to fund your bigger ambitions.

"I did not have the technical skills to pursue building something like that. So what I did instead was start DiLytics because I had the technical skills to be able to do anything in the data analytics space," he explains.

This patience paid off: "After about 9 years of running DiLytics, I managed to get the initial funding from DiLytics revenues to be able to pursue Slash in 2020."

Solving the Marketplace Chicken-and-Egg Problem

When building two-sided marketplaces, entrepreneurs often struggle with the classic chicken-and-egg problem: customers won't join without service providers, and service providers won't join without customers. Panda's solution is refreshingly practical.

"It's actually not a chicken-and-egg challenge for marketplaces. It's actually pretty clear that we have to onboard the supply side first—the service providers first," he explains.

His analogy makes the logic clear: "Whether it's an online marketplace or a physical marketplace like a brick-and-mortar shop, if you open a shop, you still need to get your stock on your shelves before you can expect customers to come into the shop and start buying."

"Whether it's a physical brick-and-mortar marketplace or an online digital marketplace doesn't matter. It always starts with the supply side—somebody who can provide goods or services. We need to first put them on the shelf before we can make a grand opening for customers to come in and start exploring."

Revolutionary Dynamic Pricing: The Slash Differentiator

While many home services marketplaces compete on convenience or quality, Slash has chosen to differentiate through something more fundamental: intelligent pricing that benefits both customers and service providers.

AI-Powered Pricing Models

Slash's core innovation lies in its dynamic pricing system that considers multiple factors to optimize both demand and supply: "We do dynamic pricing of services based on many different factors. The same haircut can be ₹500 or it can be even ₹200 depending on various different factors, but the most obvious ones are demand and supply."

The system recognizes temporal patterns: "If it's a Monday morning, then it's not a premium time for a haircut versus, let's say, a Saturday or Sunday, which is premium time when most people are available and want to get their haircuts done."

Win-Win Value Creation

The dynamic pricing model creates value for different customer segments simultaneously:

As Panda explains: "It maximizes the professionals' utilization of their working hours because there are customers filling up their working hours based on whether they are premium customers or value-driven customers. Their overall time utilization as well as earnings is optimized."

Competition with Urban Company

When asked about competing with Urban Company, India's dominant player in home services, Panda positions dynamic pricing as a fundamental differentiator rather than just a feature:

"The first and foremost key differentiator for us is dynamic pricing based on many different factors using AI models that works out very well for both customers and service providers."

This approach allows Slash to serve market segments that fixed-pricing models struggle with, creating value through intelligent resource allocation rather than just convenience.

Product-Market Fit: The Ongoing Journey

Despite Slash's innovative approach, Panda remains refreshingly honest about the challenges of achieving product-market fit in a competitive consumer marketplace.

The Non-Binary Nature of PMF

"Product-market fit is not a boolean like zero or one. It moves from zero through decimals, and nobody gets to one. Everybody has their own weaknesses and gaps that will continue to be there throughout their existence," Panda observes.

His current assessment: "I don't think there is a formula to calculate whether it's 0.5 or 0.6, but we are halfway there—roughly about halfway there. Once we make another halfway through, then we'll be ready for launch in other places."

Hyderabad Focus Strategy

Rather than spreading resources thin across multiple cities, Slash has chosen to perfect its model in one market first: "So far, we are only focused on the city of Hyderabad in India, and we are still working on product-market fit. We are making progress every couple of months in that journey."

The reasoning is efficiency-driven: "It's inefficient to launch a product in multiple cities until you have reached a certain level of product-market fit."

This patience mirrors the same strategic thinking that led him to build DiLytics first—perfect the model before scaling, rather than rushing to expand prematurely.

Future Expansion Strategy

When considering expansion beyond Hyderabad, Panda maintains a data-driven approach that balances ambition with realism.

Tier 1 Cities First

"It's too early to say that our first focus will be on the big cities, but because Hyderabad is a major city in India, that's why we are progressing on product-market fit. Once we have reached a certain level, we can be certain to a great extent that now it's going to work in other major cities like Bangalore, Delhi, Mumbai, and so on."

Tier 2 and Tier 3 Considerations

While Urban Company has focused primarily on metros, the opportunity in smaller cities remains an open question: "When it comes to tier 2 and tier 3 cities, we'll have to make some test launches and then see what tweaks we need to apply to get product-market fit at a relevant level in tier 2 and tier 3 cities. That is something that is too early for us to assess now."

This cautious optimism reflects the complexity of consumer behavior across different Indian markets—what works in metropolitan Hyderabad may require significant adaptation for smaller cities with different economic dynamics and service expectations.

Key Entrepreneurial Insights

After more than a decade of building two different companies across B2B and B2C markets, Panda offers practical wisdom that transcends industry boundaries.

The Reality of Failure Rates

Perhaps his most important insight relates to managing expectations around failure: "The biggest learning is that for everything that we try, we're going to fail a lot more than we're going to pass. If we try 100 things, we're probably going to fail at 80 things or 90 things and succeed at only 10 or 20 things."

This reality can be "pretty frustrating, pretty demoralizing," but successful entrepreneurs develop resilience: "Those who do not have the fire, the restless ambition to achieve what they set out to achieve, then they will give up."

The Persistence Imperative

"Entrepreneurship is all about recognizing that failure is going to be a default result most of the time and still being able to dust yourself off and get up and start walking again until you find what you set out to reach," Panda emphasizes.

This perspective helps explain both his patience in building DiLytics for nine years before launching Slash and his realistic approach to product-market fit as an ongoing journey rather than a binary achievement.

Key Takeaways

Shyam Panda's dual entrepreneurship journey offers several crucial insights for aspiring entrepreneurs:

Strategic Sequencing Over Simultaneous Execution: Rather than trying to build his dream consumer marketplace immediately, Panda built a profitable B2B services company first, using those revenues to fund his bigger ambition. This approach reduces risk while building entrepreneurial skills.

Leverage Domain Expertise for Initial Success: DiLytics succeeded because Panda had deep Oracle product knowledge from four years as a product manager. Starting with your strongest skills increases the probability of early success.

Supply-Side First in Marketplaces: The chicken-and-egg problem in two-sided marketplaces isn't really a dilemma—always start with supply (service providers) before focusing on demand (customers).

Product-Market Fit is a Journey, Not a Destination: Treating PMF as a continuous improvement process rather than a binary achievement helps maintain realistic expectations and sustainable progress.

Dynamic Pricing as Differentiation: Instead of competing on convenience alone, Slash uses AI-driven pricing to create value for different customer segments while optimizing service provider utilization.

Geographic Focus Before Scaling: Perfect your model in one market before expanding. Spreading resources across multiple cities before achieving local PMF is inefficient.

Cloud Adoption is Inevitable: The cloud vs. on-premise debate is settled—cloud providers' specialized expertise in security and scaling makes them superior to in-house data center management.

AI Augments Rather Than Replaces (For Now): AI is reducing data science workloads by 60-70% rather than eliminating roles entirely, while still requiring human oversight for data infrastructure.

Embrace High Failure Rates: Expecting to fail at 80-90% of attempts helps maintain psychological resilience and prevents premature giving up when encountering inevitable setbacks.

Network-Based Hiring for Early Teams: Start hiring from your professional network before building formal recruiting processes—trusted recommendations reduce early-stage hiring risks.

Panda's story demonstrates that successful entrepreneurship often requires patience, strategic thinking, and the wisdom to build bridges to your ultimate destination rather than jumping directly to the end goal. Sometimes the longest route to your dreams is actually the shortest.

About the Guest

Shyam Panda is the founder and CEO of both DiLytics and Slash. Born in Sambalpur, Odisha, he completed his engineering at NIT Rourkela and MBA at Xavier's Institute of Management, Bhubaneswar, before working in Bangalore's software industry and later at Oracle Corporation in Silicon Valley.

As a product manager for Oracle's data analytics products for four years, Panda gained deep insights into enterprise software implementation challenges, which became the foundation for DiLytics. Founded in 2011, DiLytics has grown to 92 employees and specializes in Oracle analytics solutions for mid-market customers in pharma, life sciences, and manufacturing verticals.

In 2020, using revenues generated from DiLytics' nine-year success, Panda launched Slash—a digital marketplace for home and living services featuring AI-driven dynamic pricing. Currently focused on Hyderabad, Slash offers services across beauty, home care, pet care, health & spa, tutoring, auto care, and garment care categories.

Panda's dual company approach represents a unique model of using B2B expertise to fund consumer marketplace ambitions, demonstrating the power of strategic patience in entrepreneurship.