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About Us

Revolutionizing Banking Development with Low-Code Solutions

Build, innovate, and deploy banking services effortlessly

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Our Mission and Who We Are

At 3beacons, we believe that financial innovation should be accessible to everyone. Our mission is to empower banks and FinTech companies with a low-code platform that simplifies the development of banking services, enabling rapid innovation and transformation in the financial sector.

3beacons is a team of passionate technologists and banking experts dedicated to reshaping the financial landscape. With years of experience in both technology and finance, we understand the challenges faced by traditional banking institutions and emerging FinTechs alike. Our diverse team brings a wealth of knowledge and creativity to the table, driving us to create solutions that meet the evolving needs of the industry.

Financial Solutions that Adapt to You

Our future-ready platforms evolve with emerging technologies and customer expectations. Built on a foundation of continuous innovation, they feature intelligent algorithms that dynamically adjust to your evolving needs.

Next-Generation Banking with Ethical & Secure AI

3B’s intelligent algorithms empower seamless, proactive, and customized banking operations. Intelligent automation also optimizes processes for faster, more efficient service delivery to clients.

Banking AI

Banking Simplified Through Automation

3B’s intelligent automated processes reduce manual tasks and improve operational efficiency. Automation enhances accuracy and consistency across all banking operations.

Automation

Currency Chest Automation

3B’s Currency Chest Automation Solution streamlines cash management with precision and speed. Intelligent systems optimize cash allocation based on demand and usage patterns. Robust automation improves efficiency, security, and compliance in currency chest operations.

Currency Chest Automation

Latest Blog

By Dr. Abhijeet Malge, Dean – MIT

ResNet-based UNet++ GAN: A Step Forward in High-Resolution Image Generation

Generative Adversarial Networks (GANs) have redefined image synthesis, powering applications from medical imaging to computer vision. Traditional models such as Wasserstein GANs and Progressive GANs improved stability and resolution but often fell short in preserving fine details and structural consistency.

A new approach, the ResNet-based UNet++ GAN, combines the strengths of residual learning with the nested skip connections of UNet++. Residual blocks enhance training stability and feature reuse, while the UNet++ architecture captures multi-scale contextual information through its dense skip pathways. This hybrid design enables the generator to retain intricate spatial details, producing sharper and more realistic images.

Evaluations across datasets like CelebA and CIFAR-10 show that the ResNet-based UNet++ GAN surpasses earlier architectures in both visual quality and accuracy. By addressing limitations of existing GANs, this model paves the way for robust, high-fidelity image generation, making it highly relevant for domains requiring precision and realism.