We design intelligent systems that learn, adapt, and create. Whether you're building a smart recommendation engine, training a custom LLM, or launching a GPT-powered chatbot — we bring your AI ideas to life with precision and care.
From classical machine learning to cutting-edge GenAI workflows, we build scalable pipelines using OpenAI, Hugging Face, LangChain, Pinecone, TensorFlow, and beyond.
Service Overview
Our AI/ML & GenAI team helps you go from prototype to production — whether you're fine-tuning open-source models or integrating third-party LLM APIs. We design workflows that are robust, privacy-respecting, and ready to scale with real-world data.
We also help clients evaluate use cases, reduce hallucinations, optimize vector search, and deploy models securely with CI/CD and MLOps best practices. From embedding GPT-4 for customer support to building private RAG systems with LangChain and Weaviate — we build systems that actually deliver value.
Our approach is pragmatic: we balance custom model training with off-the-shelf LLMs (OpenAI, Claude, Mistral) and deploy them using scalable infrastructure like AWS SageMaker, Docker, and FastAPI. Whether you're generating code, text, insights, or embeddings — we turn models into production-ready services.
We also provide prompt engineering, fine-tuning pipelines, secure retrieval-augmented generation (RAG), and MLOps setup — helping you continuously improve model performance and reduce operational risks.
Whether you're a SaaS product building intelligent features, an enterprise automating workflows, or a startup launching your own AI agent — we bring the strategy, the code, and the infrastructure.
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Years of experience this field
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Number of projects completed
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Number of awards achieved
Key Features
We build smart systems with real-world impact — personalized, performant, and aligned with your business goals.
- GPT/LLM Integrations (OpenAI, Claude, Mistral, Mixtral)
- Custom Fine-Tuning & Prompt Engineering
- RAG Pipelines with LangChain & Vector DBs (Pinecone, Weaviate)
- ML Model Training (scikit-learn, TensorFlow, XGBoost)
- MLOps & Deployment (Docker, FastAPI, Airflow, SageMaker)
