Langchain empowers developers to build context-aware, multi-step applications using large language models (LLMs). At Tatvaflow, we utilize Langchain to create intelligent workflows, dynamic agents, and advanced automation pipelines that integrate seamlessly with APIs, databases, and other tools—turning AI into real-world solutions.
Book a Consultation Call Book a Consultation CallOur Langchain expertise helps you build powerful, intelligent, and adaptable applications that fully leverage the capabilities of modern LLMs.
We build custom AI applications using Langchain that perform intelligent reasoning, content generation, and language understanding with seamless data source integration.
Our team creates autonomous agents that make decisions, call tools, and handle multi-step tasks using Langchain’s ReAct framework and memory management features.
We implement RAG pipelines that combine LLMs with document stores or databases, enabling dynamic, context-aware answers using your internal knowledge.
We integrate Langchain with APIs, search engines, CRMs, and vector databases, empowering your AI to interact with real-time business tools.
Our developers create intelligent, memory-powered chatbots using Langchain for customer support, HR, education, and more—capable of following context and multi-turn conversations.
We build systems that connect Langchain with PDFs, Notion, Google Drive, or custom datasets—letting AI reason over business-specific documents securely.
We help you integrate fine-tuned open-source LLMs into your Langchain pipelines for domain-specific use cases like legal, medical, and financial applications.
We create scalable AI pipelines by combining Langchain with vector databases like Pinecone, Qdrant, and FAISS to enable fast, intelligent search and recommendations.
Development engagement models offer flexible collaboration approaches, ensuring tailored solutions to meet unique project requirements efficiently.
Our Langchain developers utilize a rich ecosystem of technologies to craft robust, responsive, and intelligent AI systems—from prompt engineering to vector search and cloud deployment.
To build full-featured AI applications, we combine Langchain with a powerful mix of LLMs, storage tools, and backend technologies for real-time execution and scalability.
Development engagement models offer flexible collaboration approaches, ensuring tailored solutions to meet unique project requirements efficiently.
View all case studiesDeveloped an AI-driven system for real-time detection and management of parking spots, improving urban parking efficiency and reducing congestion.
Created a deep learning-based web tool to accurately classify various hair and scalp diseases, aiding early diagnosis and medical education.
Developed an AI chatbot enabling seamless interaction with multi-format documents, enhancing information retrieval and user engagement.
Implemented an LSTM-based deep learning model to predict stock prices, helping users make informed investment decisions through accurate forecasting.
Developed a face recognition-based automated attendance system to enhance accuracy and efficiency in managing attendance records in real time.
Implemented an AI-driven tool to analyze customer feedback, providing sentiment analysis and trend detection to help businesses improve customer satisfaction.
Developed a real-time license plate recognition system to automate vehicle identification, enhancing security and traffic management efficiency.
Created a personalized learning recommendation engine to tailor educational content based on student performance and preferences, boosting engagement and outcomes.
Developed an AI chatbot to automatically summarize complex legal documents, making legal information more accessible and easier to understand for users.
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Achieved a remarkable 92% improvement in diagnostic accuracy, ensuring reliable results
Reduced diagnosis time by 85%, enabling faster clinical decisions and patient care
Accuracy in facial recognition across diverse conditions
Reduction in attendance processing time