Seed Lab
In today’s AI-driven world, data is the foundation of intelligence. Artificial Intelligence systems depend not merely on the volume of data, but on its quality, accuracy, and diversity. The data used to train AI models defines how effectively systems understand the world, make decisions, and deliver meaningful outcomes.
At our institution, we recognize that structured data generation and synthetic data creation are transformative components of modern AI development. Synthetic data refers to artificially generated datasets created through algorithms and simulations, enabling scalable, ethical, and high-quality training environments. Data Generation (DG) initiatives focus on producing large-scale, precise, and application-ready datasets — including annotated images, videos, and textual information — to power next-generation AI solutions.
This lab stands as a collaborative platform connecting academia, research professionals, and industry leaders to accelerate innovation in Artificial Intelligence and Data Science.
Unveiling the Possibilities:
The Data Generation & AI Innovation Lab opens new avenues for collaboration, research, and real-world implementation:
Strategic collaboration on AI and Data Science projects aligned with industry needs.
End-to-end mentorship and guidance under SRI-B framework, from ideation to execution.
Exposure to real-time problem statements and scalable AI deployment strategies.
Industry-integrated workflows that simulate professional AI development environments.
This initiative ensures that students and researchers gain practical exposure while contributing meaningfully to impactful AI solutions.
Innovation on the Horizon:
The lab is designed to stay at the forefront of technological advancements by:
Adapting to emerging domains such as 3D data modeling, AR/VR technologies, and immersive AI applications.
Continuously upgrading tools and methodologies to remain aligned with global technology trends.
Encouraging innovation-driven research that anticipates future industry requirements.
Our commitment is to build an ecosystem that evolves with the rapidly transforming digital landscape.
Industry-Focused Projects
The lab operates on structured and transparent project frameworks to ensure clarity and measurable outcomes:
Industry requirements are defined through a detailed Statement of Work (SOW).
Execution of advanced AI tasks including:
Image and video data capturing
Text annotation and processing
Labeled dataset creation
Computer vision and machine learning data preparation
This structured approach ensures quality, scalability, and professional project delivery standards.
State-of-the-Art Infrastructure:
The Data Generation & AI Innovation Lab is supported by advanced infrastructure designed for high-performance computing and collaborative innovation:
Lab 1: Spanning 1,800 sq. ft. with specialized AI workstations.
Lab 2: Spanning 3,000 sq. ft. equipped with cutting-edge computing resources.
High-performance servers and scalable data storage systems.
Advanced data processing tools and AI development platforms.
Dedicated research and collaboration spaces to foster innovation.
The infrastructure enables seamless execution of large-scale data generation and AI development projects.
SEED Lab Community & Growth
The SEED Lab ecosystem reflects rapid and sustainable growth:
Expanded from 35 to 185 employees within six months, demonstrating strong industry trust and operational scalability.
Welcoming graduates from BE, BCA, and MCA programs for diverse and dynamic career opportunities.
Promoting a culture of innovation, collaboration, and continuous skill enhancement.
The community-driven model ensures both academic enrichment and professional excellence.
Driving the Future of Intelligent Systems
The Data Generation & AI Innovation Lab is more than an academic facility — it is a center of excellence in AI research, data engineering, and industry collaboration. By integrating high-quality data practices with forward-thinking innovation, the lab is actively shaping the future of intelligent technologies.
