Driving software innovation and research, working remotely with a global reach

Innovating, researching, and building next-gen software solutions.

OTHERS CHASE TRENDS.
WE ENGINEER MOMENTUM.

OTHERS CHASE TRENDS.
WE ENGINEER MOMENTUM.

OTHERS CHASE TRENDS.
WE ENGINEER MOMENTUM.

At R3ACTR, we specialize in building innovative software solutions, research-driven projects, and cutting-edge web experiences. From AI and Web3 applications to SaaS platforms, our goal is to create products that make a real impact.

We combine creativity, technology, and research to craft software that is not only functional but also intelligent, scalable, and user-friendly. Whether designing sleek interfaces, developing complex applications, or exploring emerging technologies, our team is always pushing the boundaries of what’s possible.

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Beyond development, R3ACTR thrives on collaboration and knowledge-sharing. We actively engage with tech communities, contribute to research, and mentor upcoming talent, ensuring our work is informed, innovative, and impactful.

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Founders

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ABHINAV R.

Co-Founder @ R3ACTR

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SREEHARI R.

Co-Founder @ R3ACTR

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KALIDAS V.

Co-Founder @ R3ACTR

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NEERAJ S.

Co-Founder @ R3ACTR

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Flagship Event

Open Source Quest

Open Source Quest

Open Source Quest is a structured, month-long open-source contribution program designed to help students gain real-world experience with professional software development workflows.

Participants work individually on curated, domain-specific GitHub repositories under guided mentorship. The program focuses on understanding how real open-source projects function—through issues, pull requests, reviews, and consistent contributions—rather than competitive coding or short-term hackathons.

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Publications

ADA-XAI: Adaptive Faithfulness-Driven Explainability for Hybrid EVA-02 and Deformable CNNS in Brain Tumor Diagnosis From MRI Images

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CRDA: Cross-Reasoning Disagreement Analysis for Uncertainty Quantification in Hybrid Voice Classification

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Pixel-Level Supervision for Medical Imaging: A Custom Masked Autoencoder Framework for Renal Pathology Detection

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