BlueBuck Research bridges rigorous AI/ML research with real-world product engineering — helping enterprises build intelligent systems that compound value over time.
From foundational AI research to production deployment — we cover every layer of intelligent system development.
Custom LLM pipelines, fine-tuning, RAG architectures, and autonomous AI agents.
Statistical modelling, predictive analytics, and custom ML research.
Full-stack product development from concept to launch — AI integration built in.
Production-grade ML infrastructure, automated retraining, cloud-native deployments.
Autonomous agents that can research topics, summarize documents, and execute specific multi-step workflows.
Enterprise-grade Retrieval Augmented Generation pipelines that root LLM answers in your secure, proprietary data.
Context-aware AI assistants embedded directly into your software products to augment user productivity.
Custom model alignment to ensure the AI perfectly understands your domain terminology and brand voice.
Turn passive historical data into active, high-accuracy predictions to optimize inventory and pricing.
Rapid scoping, architecture, and deployment of a working AI proof-of-concept before full-scale investment.
AI systems and digital products that solve real business problems — measurably.
A custom machine learning model integrated into core banking systems to predict default probability with high accuracy.
An intelligent document processing system that extracts critical patient history from unstructured clinical notes.
An autonomous agent that handles first-notice-of-loss, validates damage via computer vision, and routes complex claims.
Time-series forecasting models using deep learning to predict demand patterns across 10,000+ SKUs globally.
A personalized conversational tutor that adapts to student learning paces and explains concepts interactively.
A real-time recommendation system handling millions of user interactions to serve hyper-personalized product suggestions.
We embed dedicated AI/ML engineers and researchers into your workflows, giving you instant capacity without the 6-month hiring delay.
Rigorous feasibility studies, architecture design, and roadmapping before you write a single line of production code.
Continuous model monitoring, retraining, and R&D iterations to ensure your AI systems compound in value over time.
We measure our success not by the complexity of the models we build, but by the tangible business value they create. Our team has engineered intelligent systems for industries ranging from healthcare to finance.
Every deployment is backed by rigorous testing, dedicated research engineers, and a commitment to long-term compounding value.
Rapid prototyping and scalable architecture for fast-growing tech companies.
Compliance-ready, highly secure AI deployments integrated into legacy systems.
Collaborative R&D projects pushing the boundaries of applied machine learning.
We are a collective of ML engineers, data scientists, and full-stack developers. Founded in Kolkata, India's intellectual capital, we prioritize rigorous thinking and flawless execution above all else.
Weekly deep dives into the latest arXiv papers and models.
No-meeting blocks to ensure uninterrupted engineering flow.
Dedicated budgets for cloud certs, courses, and conferences.
We remain stack-agnostic, choosing the right combination of state-of-the-art research models and bulletproof enterprise engineering tools for every project.
"BlueBuck didn't just build a model; they re-architected how we approach credit risk. The AI engine now handles ₹500Cr+ in daily decisioning with 99.8% uptime."
"What impressed us most was their rigorous testing methodology. The Clinical NLP platform was delivered in 8 weeks and reduced manual review by 80%."
"Unlike generic AI agencies, BlueBuck understands production realities. Their computer vision agent for touchless claims is now processing 60% of our volume."
"The predictive engine they built for our supply chain forecasting achieved 94% accuracy, directly translating to a 35% reduction in carrying costs."
This guide cuts through the hype. Vector similarity search alone fails in complex enterprise scenarios. Learn how to implement hybrid search algorithms and graph-based retrieval to ground your production LLMs.
Everything you need to know about our research methodology, engagement models, and AI engineering practices.
We are an AI research lab first. We don't just glue together OpenAI APIs; we build custom predictive models, fine-tune LLMs on proprietary data, and architect deep-tech solutions that generalist agencies cannot execute.
Whether you need a custom LLM fine-tuned on your data, or a predictive analytics engine to optimize costs, our research engineers are ready to build it.
Sector V, Salt Lake City
West Bengal 700091