Case Study #15: See How DSW Helps Enterprises Reduce Cost of Ownership by 30% and Halves AI Deployment Times

Since 2019, Data Science Wizards has been turning AI experiments into real business value for enterprises. Their UnifyAI platform cuts costs by 30% and halves deployment times, turning AI experiments into business value. Operating from Mumbai and Dublin, they're making AI work for businesses, not the other way around.

Company:
Data Science Wizards (DSW)

Founded:
2019

Headquarters:
Dublin, Ireland, and Mumbai, India

Key Highlights:

Slashed enterprise AI costs by 30% and halved deployment times
Secured major insurance company as first production pilot client
Expanded from BFSI to healthcare, retail, and manufacturing sectors
Integrated AI and GenAI capabilities into unified enterprise platform
Positioned for marketplace offerings on Intel, IBM, AWS, Azure, etc
Achieved $500,000 annual revenue at the pre-Series A stage

1. Hello! Tell us who you are and what's your backstory?

Hi there! I’m Pritesh, the founder and Chief Data Scientist at Data Science Wizards (DSW) and one of the visionaries behind UnifyAI. My journey began in the vibrant city of Mumbai, where I grew up with a fascination for technology and its potential to drive change. After completing my Master's in Data Analytics from the National College of Ireland in Dublin, I embarked on a career that spanned AI and Data Science in Banking, Insurance, and Financial Analysis.

My key influences were the dynamic nature of data science and the endless possibilities it offered for innovation. These experiences and a drive to push the boundaries of what AI can achieve led me to become a techpreneur.

Before founding DSW and embarking on the journey of building our Enterprise Grade GenAI Platform - UnifyAI, I was deeply involved in setting up and scaling an AI and Innovation team in a multinational insurance company, which solidified my passion for transforming industries with AI.

‍2. Can you give us your 1-3 sentence elevator pitch?

We're DSW UnifyAI: Our enterprise-grade GenAI platform rapidly develops and scales AI-powered solutions, from data integration to deployment. Designed as an end-to-end solution, our platform unifies AI capabilities to help businesses enhance efficiency and innovation to build industry-specific use cases with speed, scalability, and predictability. The platform brings up to a 30% reduction in TCO and cuts down production time by over 50% for every new use case built.

3. What was the moment or situation that sparked the idea for your business?

The idea for Data Science Wizards (DSW) was sparked by a confluence of experiences and realizations we encountered while providing AI services and consulting to clients in the BFSI sector and beyond. As a team of founders with deep expertise in Insurance, Banking, Open source, AI, and Data Science, we initially focused on delivering tailored AI solutions to solve specific client challenges. However, we quickly noticed a recurring theme: many businesses struggled with the transition from AI experimentation to scalable production. They faced challenges in integrating AI models into their existing workflows, dealing with data complexity, and maintaining consistency across deployments.

Our 'aha' moment came during a project with a major insurance company. Despite the successful delivery of AI models, we observed that our clients needed more support in deploying these solutions effectively at scale. This realization led us to conceptualize UnifyAI, a platform designed to streamline the AI journey from experimentation to production, addressing the scalability and integration issues that many organizations face. We were driven by the vision of creating a seamless AI ecosystem that empowers enterprises to harness AI’s full potential without the typical obstacles of complexity and inconsistency.

‍4. How did you test and refine your initial product idea, and were there any significant pivots or changes in direction based on initial feedback or market response?

Our journey from concept to validation for UnifyAI was both insightful and challenging. We began by developing a Minimum Viable Product (MVP) that encapsulated our core idea—providing an integrated AI platform that simplifies the transition from experimentation to production. The MVP was released as UnifyAI v0 in April 2022, allowing us to gather critical feedback from a select group of early adopters and industry experts.

During the initial testing phase, we collaborated closely with one of India's largest insurance companies to implement a production pilot use case focused on "persistence." This pilot provided invaluable insights into the real-world application of our platform and highlighted areas for improvement. Based on the feedback received, we iterated on the platform's features, enhancing data integration capabilities, optimizing model deployment workflows, and refining the user interface for better accessibility and efficiency.

One significant pivot we made was in our approach to scalability. Initially, we underestimated the complexity of scaling AI models across different environments and industries. By actively engaging with our pilot customers, we realized the need for more robust orchestration features and automated pipelines. These enhancements were integrated into UnifyAI v1, which was released in August 2023, marking a significant evolution in our platform's capabilities.

Later we added AI Studio and GenAI Studio to accelerate the journey of building the use cases and going into production and making it easy for enterprises to leverage GenAI capabilities.

‍5. What specific strategies or decisions significantly contributed to the growth and scaling of your business?

Several strategic decisions and approaches have significantly contributed to the growth and scaling of our business:

Building Strategic Partnerships: Early on, we recognized the value of forming strategic alliances with key players in the BFSI sector. These partnerships allowed us to demonstrate our platform’s effectiveness in real-world scenarios, providing credibility and trust that attracted new clients.

Focusing on Customer Success: We placed a strong emphasis on customer success by offering personalized support and continuous engagement. By ensuring that our clients derived tangible value from our platform, we cultivated long-term relationships and fostered customer loyalty, leading to long-term engagement, referrals, and growth.

Investing in R&D: We committed resources to research and development to stay ahead of technological advancements and industry trends. By continuously innovating and enhancing our platform's capabilities, we maintained a competitive edge and addressed emerging market needs.

Targeted Marketing and Thought Leadership: Our marketing strategy focused on establishing DSW as thought leaders in the AI domain. Through articles, events, publications, and participation in industry conferences, we positioned ourselves as experts, gaining visibility and attracting potential clients interested in leveraging AI for their business needs.

Expanding Service Offerings: Initially focused on BFSI, we expanded our offerings to other sectors such as healthcare, retail, and manufacturing. This diversification allowed us to tap into new markets and broaden our client base.

6. Can you share some major challenges and how you tackled them?

As enterprises increasingly recognize the potential of AI, they often encounter significant hurdles in adoption. One of the major challenges we've observed is the difficulty in integrating AI solutions into existing workflows and overcoming entrenched processes. Many organizations find it challenging to transition from traditional methods to AI-driven systems due to concerns about complexity, scalability, and the perceived risk of disrupting established practices.

To address these issues, we focused on building trust and demonstrating tangible value through targeted pilot programs. For example, our collaboration with one of India’s largest insurance companies began with a production pilot use case centered on "persistency." This approach allowed us to showcase the practical benefits of our AI solutions in a real-world context, addressing concerns and highlighting how AI could seamlessly integrate into their existing processes.

By delivering measurable results and incorporating feedback from these pilot projects, we were able to demonstrate the effectiveness of AI and facilitate a smoother transition for enterprises. This approach not only helped in overcoming initial resistance but also fostered a deeper commitment from our clients to adopt and scale AI-driven solutions within their organizations.

‍7. How did you really get to know your customers and market?

Customers -> UnifyAI is targeted to three key categories of customers:

AI Advanced: Enterprise Customers with existing AI use cases already in production or planning on scale-up of AI use cases

AI Ready: Enterprise Customers with existing Data Science teams and assigned AI budgets for adoption

AI Emerging: Enterprise Customers with possible teams and AI budgets, but no implementations or set plans in place

UnifyAI is designed to cater to all the above target customers with varying platform propositions, implementation models, and in-house data scientists to enable swift building, scaling, and monitoring of AI business value chain use cases.

Market Potential-> The TAM for Artificial Intelligence (AI) is valued at USD 2 T by 2032 at a compound annual growth rate (CAGR) of 34.86% from 2022 to 2032

The SAM (Serviceable Available Market) for AI Platforms by 2032 is valued at USD 254 B

UnifyAI’s Obtainable Projected Market SOM - USD 100M (SOM – Serviceable Obtainable Market realistically captured as per capabilities and projections)

Regions targeted are Europe, India, the USA, the Middle East

‍8. What's the story behind your brand and marketing approach?

The story behind Data Science Wizards (DSW) and our brand's identity is rooted in our deep expertise and passion for transforming industries through AI. Our journey began with a mission to address the gaps in AI adoption faced by enterprises, particularly in sectors like BFSI. As we observed firsthand the challenges organizations faced in integrating AI solutions, we realized the need for a platform that could simplify this transition and provide a comprehensive AI ecosystem. This realization led to the creation of UnifyAI, a platform designed to seamlessly bridge the gap between AI experimentation and scalable production.

Unique Marketing Strategies include:

Thought Leadership: We establish our authority through blogs, webinars, and industry events.

Case Studies: Highlighting real-world success stories to showcase the tangible benefits of our platform.

Workshops and Demos: Offering hands-on experiences to demonstrate UnifyAI’s capabilities.

Strategic Partnerships: Collaborating with industry leaders to build credibility and reach.

Social Media Engagement: Sharing updates and insights to build brand presence and drive interest.

‍9. How did you attract and secure your first customers?

Attracting our first customers was a pivotal moment in our journey. We leveraged our existing network and industry experience to reach out to potential clients in the BFSI sector. Our initial strategy involved:

Personalized Outreach: We conducted targeted outreach to decision-makers within financial institutions, presenting tailored solutions that addressed their specific challenges. This approach resonated well, as it demonstrated our understanding of their unique needs.

Showcasing Proven Success: We highlighted successful case studies and pilot projects that demonstrated the tangible benefits of our AI solutions. By showcasing real-world results, we built credibility and instilled confidence in our capabilities.

Offering Platform Demos: To build trust and demonstrate our expertise, we offer free workshops and demos. These sessions provided an opportunity for potential clients to the value of our platform firsthand, leading to successful engagements.

Leveraging Thought Leadership: As recognized AI mentors and trainers, we utilized our thought leadership positions to connect with industry professionals and influencers. By sharing insights and trends through blogs, webinars, and conferences, we attracted attention from organizations seeking AI-driven solutions.

‍10. What's been your approach to product development?

Our approach to product development is centered around iterative improvement and customer feedback. For UnifyAI, we started with an MVP (version v0) to test our core ideas and gather initial feedback. This feedback was crucial in refining our product, leading to the development of UnifyAI v1. Throughout the process, we engaged closely with our early adopters and production customers to understand their needs and pain points. This iterative approach allowed us to enhance the platform's features and capabilities, ensuring it met the demands of real-world applications and provided a seamless transition from experimentation to production.

‍11. What are the top 3 products/tools that have had the biggest impact on running your business?

Github, Google Workspace, Opensource tools

‍12. How are you leveraging AI to cut costs in your business?

AI is at the heart of our cost-cutting strategy. By utilizing open-source AI tools for automation, we’ve significantly reduced manual efforts and operational costs. For example, our platform, UnifyAI, incorporates advanced algorithms to streamline data integration, feature engineering, and model orchestration, which reduces the time and resources required for these processes. Additionally, by optimizing our AI workflows and enhancing the efficiency of our operations, we’ve been able to reduce the total cost of ownership (TCO) by 30% and shorten deployment times by 40%.‍

13. How have you navigated the financial aspects of your business?

Navigating the financial aspects of a startup involves a careful balance of budgeting, funding, and financial growth. Initially, we secured funding through a mix of seed investment and strategic partnerships. As we scaled, we focused on maintaining a lean budget and prioritizing expenditures that aligned with our growth strategy. Financial discipline and regular monitoring of our cash flow allowed us to reinvest in product development and customer acquisition. We also leveraged financial projections and performance metrics to make informed decisions, ensuring sustainable growth and long-term success.

‍14. What future do you envision for your company?‍

Next on the horizon - The platform is slated to release as a marketplace offering which will be enlisted on: Intel, IBM, AWS, Azure, OCI, and Guidewire. Recently, DSW UnifyAI has been introduced to select target customers through a Production Pilot Program - an initiative designed to lower barriers to AI adoption and reduce experimentation costs for customers. Program includes: Full access to UnifyAI platform for 6 months, First use case built by DSW, Assistance to customer team while they build further use cases within 6 months from production pilot start date, Dedicated Data Scientist, 24x7 email support.

This program aims to help businesses quickly and efficiently build, deploy, and manage AI use cases, showcasing the potential of UnifyAI. To meet growing demands and an expanding user base, UnifyAI will transition to a SaaS-based AI Cloud model by January 2025. This shift will enable scalable, use case-driven, and inferences-based consumption, enhancing support for enterprise customers.

‍15. Is your team growing? Tell us about the roles you’re looking to fill.

Yes, our team is indeed growing as we continue to expand our reach and capabilities. We are actively seeking talented individuals who share our passion for innovation and excellence in AI. Here are some of the roles we’re looking to fill:

Data Scientists: We're searching for data scientists who have a strong background in machine learning and deep learning algorithms, with experience in building and deploying scalable models.

Sales and Business Development: We're expanding our sales team to reach new markets and engage with potential clients, seeking individuals with a proven track record in enterprise sales and a passion for AI solutions.

DSW Team @ Dublin Tech Summit 2024.

16. Where can curious minds find more information about your business?

Explore more about us and our innovations:

Website: DSW UnifyAI

Product Update: AI Transformation in Enterprises

Company Profiles:

AI Data Hub: Community Newsletter

17. Do you have any reflections or insights you’d like to share with our community?

One key insight I’d like to share is the importance of resilience and adaptability in entrepreneurship. The journey is often filled with unexpected challenges and changes. Embracing these challenges as opportunities for growth and remaining flexible in your approach can make a significant difference. Additionally, fostering strong relationships with your customers and partners, and valuing their feedback, is crucial for continuous improvement and success. The path to building something impactful is rarely linear, but with perseverance and a commitment to innovation, it’s incredibly rewarding.

‍18. How will the rapid advancement of AI reshape society and the world over the next decade, and what are the key implications?

As someone deeply involved in the AI industry, I believe the rapid advancement of AI will transform industries by automating processes, improving decision-making with data-driven insights, and enriching daily life with personalized experiences. However, this progress comes with significant challenges, such as potential job displacement, ethical concerns about AI governance, and the risk of increased economic disparities. It's essential that we balance innovation with responsible development to navigate these issues effectively.

‍19. Can we create artificial general intelligence (AGI) that matches or exceeds human intelligence across many domains?

Yes, creating Artificial General Intelligence (AGI) that matches or even exceeds human intelligence across multiple domains is an achievable goal. As technological advancements continue at an exponential pace, we're witnessing significant strides in AI research and development. The convergence of machine learning, neuroscience, and computational power has laid a strong foundation for AGI.

AI systems are already outperforming humans in specific tasks such as image recognition, natural language processing, and strategic game-playing. With the ongoing research in areas like deep learning, reinforcement learning, and neural networks, the path to AGI is becoming increasingly clear.

Researchers are focused on building systems that not only solve specific problems but also possess the ability to learn, reason, and adapt across various domains autonomously. As we enhance our understanding of human cognition and replicate it in machines, AGI is not just a possibility—it’s an inevitable reality.

This journey requires overcoming complex challenges, such as developing AI that understands context, exhibits emotional intelligence, and learns from minimal data. However, given the rapid progress in AI, it is only a matter of time before we achieve AGI capable of performing at or above human-level intelligence across diverse fields. The future of AGI is not a question of if, but when.

‍20. How can we ensure advanced AI systems are safe, ethical, and aligned with human values?

Building safe and ethical AI is a complex puzzle with no easy solutions. We need to rigorously test these systems from every angle, making sure they're transparent and can explain their reasoning. It's not just about the tech; we need strong ethical guidelines and open dialogue between industry, policymakers, and ethicists. We're playing with fire here, so we need to be incredibly careful.

‍21. What are the fundamental limits of AI's capabilities compared to human intelligence?

AI is a powerful tool, no doubt, but it's a tool. It's incredibly good at crunching numbers and finding patterns, but it doesn't truly understand things the way we do. It lacks that gut feeling, that spark of creativity, that ability to adapt on the fly. AI is brilliant at what it does, but it's not human. We need to be clear-eyed about its strengths and limitations. AI is a powerful ally, but it's not a replacement for human ingenuity.

Interview with
Sandhya Oza
Co-founder and Chief Project Officer @ Data Science Wizards

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