No Code AI Platform for Data Analysis
FinanceTransforming Data Analysis with Generative AI
About No Code AI Platform for Data Analysis
The AI born startup is a pioneering technology company positioned at the cutting edge of data science innovation. With a strong focus on developing a sophisticated no-code data science platform, the AI startup strives to eliminate the barriers traditionally associated with data analysis. This approach enables a broader audience to engage with data analytics, fostering a culture of data-driven decision-making across various sectors without the need for extensive technical training.
The Challenge
The primary challenge the AI startup company aimed to address was the technical skills gap in data analysis, which prevented a wide range of users from engaging in advanced data analytics. Traditional data analysis tools often require significant coding knowledge and data science expertise, creating barriers to entry for individuals and organizations without these skills. The AI startup sought to democratize data analysis by developing a no-code platform that simplifies complex data analysis processes, making it accessible to users irrespective of their technical background.
Our Goals
Central to the development and realization of AI startup’s ambitious goals is the partnership with AntStack, a team renowned for their expertise in leveraging cutting-edge serverless technology. Our team was tasked to build a platform that the platform is scalable, cost-effective, and user-friendly, making advanced data analysis accessible to a broader audience. Our’s commitment to excellence and our forward-thinking approach are key to navigating the challenges and complexities of this project, setting a new standard in the field of data science.
Goals:
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Simplify Data Analysis - Make advanced data analysis accessible to a wider audience by removing the need for coding and extensive data science expertise. Broaden the user base for data analytics by offering a platform that is easy to use for individuals with non-technical backgrounds.
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Innovative Platform Design - Develop a platform with a user-friendly interface that integrates seamlessly with various data sources, supports automated data cleansing and transformation, and offers an intuitive no-code analysis engine.
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Rapid Deployment - Develop and deploy a Minimum Viable Product (MVP) within a shortened timeline to quickly address market needs and gather user feedback.
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Reduce Operational Costs - Utilize serverless architecture to minimize setup and operational costs, making the platform economically viable for a wide range of users.
Challenges Faced and Solutions:
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Response Time Limitations - The primary challenge AntStack team encountered was related to response time limitations. The response time of GPT, while highly effective, exceeded the API Gateway’s time limit of 30 seconds. To overcome this, we established a workaround by communicating with the frontend through functional URLs, ensuring users received timely responses without compromising user experience.
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Library Size and Lambda Layers - Building the core features of the platform using Langchain resulted in larger library sizes, which surpassed the Lambda layers limit. This forced us to pivot to an alternative approach and deploy Lambda functions using containers, allowing us to manage and accommodate the required libraries while ensuring platform functionality.
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Testing with Langchain - Langchain, being a relatively new library, presented challenges in writing comprehensive test cases. Ensuring good test coverage was essential for the reliability and stability of the platform, making it necessary to invest extra effort in testing and quality assurance.
These challenges, while demanding, were met with innovative solutions, adaptability, and a commitment to delivering a high-quality, fully functional data science platform.
These lessons will guide us in future endeavors, inspiring us to remain adaptable, innovative, and dedicated to delivering exceptional solutions that meet the evolving needs of our clients and the dynamic landscape of technology.
Impact
3x Faster Building and Deployment of MVP
AntStack’s adoption of a serverless architecture had a remarkable impact on the project’s development timeline. Thanks to the serverless approach, the project achieved a threefold increase in speed when building and deploying the Minimum Viable Product (MVP). The application was not only rapidly developed but was also production-ready in less than 3 months. This swift progress allowed the project to seize market opportunities sooner, gain an edge in time-to-market, and promptly gather user feedback for further enhancements.
3X Lower Cost of Operations per User and Lower End Customer Pricing
AntStack’s serverless approach brought about a substantial reduction in operational costs, resulting in a threefold decrease in the cost of operations per user. This efficiency translated into a threefold reduction in end customer pricing. By offering significantly lower pricing, the project’s product became more cost-effective and attractive to end customers. The project’s ability to provide such competitive pricing, coupled with the benefits of serverless technology, contributed to higher user adoption and customer satisfaction.
A Startup within Organization
The successful development and launch of the AI Startup’s no-code data science platform, spearheaded by the AntStack team, marks a significant milestone in the democratization of data analysis. By making advanced analytics accessible to a broader audience and reducing operational costs, the platform not only meets its core objectives but also sets a new standard for innovation in the field. This achievement paves the way for future advancements, signalling a bright future for accessible data analysis.
