Moweb Limited

From Scattered Knowledge to Smart Business Decisions: Production-Ready Enterprise LLM and RAG Solutions

Today, enterprises are no longer asking if they should adopt AI, but how fast they can do it safely and effectively. We build RAG and LLM-based chatbots, autonomous agents, and secure MCP(Model Context Protocol)-integrated systems that deliver real business outcomes while maintaining total control and transparency. With our proven frameworks, your organization can leverage AI for faster decision-making, smarter customer engagement, and scalable operational efficiency.

We bridge the gap between experimentation and enterprise-grade deployment, crafting solutions that move from innovation to impact.

Production-ready chatbots, RAG pipelines, and voice assistants with Natural Language Processing (NLP) from fast POCs to low-risk production

Tailored conversational workflows with enterprise-grade security and MCP integrations

Automated knowledge discovery through contextual retrieval and semantic search

Measurable business ROI with reduced response time and improved customer satisfaction

Value Proposition

The problem we solve

Fragmented knowledge systems, prolonged support SLAs, and a lack of intelligent domain-aware assistants across business functions.

Our core capabilities

Retrieval-Augmented Generation (RAG), LLMs for enterprise, prompt engineering, embeddings, vector database integrations, multi-lingual pipelines, enterprise RAG solutions, and speech systems.

Outcome examples

60% faster support resolution, 40% fewer escalations, improved knowledge findability with up to 95% semantic search accuracy, and context-aware responses.

Why RAG & Conversational AI now

Organizations are flooded with unstructured information scattered across emails, documents, CRM logs, and knowledge repositories. Retrieval-Augmented Generation (RAG) and LLMs for enterprise are transforming this chaos into intelligent, accessible insights.

Businesses are using Conversational AI to automate support, augment employees with knowledge bots, and accelerate enterprise decisions. The rise of frameworks like LangChain, LangSmith, and MCP has made secure integrations and MLOps partner for enterprise easier than ever.

Now, enterprises can deploy RAG-based assistants, semantic search tools, and enterprise LLM chatbot development that deliver measurable performance and compliance, bridging human knowledge with machine intelligence in real time.

Our Offerings

RAG pipelines & document ingestion

Custom chatbots & virtual assistants

Enterprise knowledge bases + semantic search

Multilingual support & localization

Voice assistants (STT/TTS pipelines)

Prompt engineering & persona design

Embeddings generation & vector database management

LLM fine-tuning / PEFT (LoRA / QLoRA) for domain adaptation

Secure integrations & MLOps for enterprise

LangChain-powered workflow orchestration via MCP

Ready to Transform Your Enterprise Knowledge into Intelligent Action?

Request a demo to see production-ready RAG pipelines and enterprise chatbots in action

Schedule a call with us

How We Build: Our Technical Approach

We follow a structured, MLOps-driven lifecycle for building scalable, enterprise-grade GenAI systems. From proof-of-concept (POC) to secure deployment, our Conversational AI & RAG architecture ensures adaptability and performance within enterprise environments. Our team applies principles of Retrieval-Augmented Generation to enrich LLMs for enterprise with verified, contextual data rather than relying solely on pretrained knowledge.

This approach ensures every knowledge bot, enterprise chatbot, or voice assistant powered by Natural Language Processing (NLP) operates within a secure, low-latency, and high-performance environment tailored to your business objectives.

Discovery & Design

Understanding business KPIs, knowledge domains, and the existing data repository.

Data Preparation

Setting up ingestion pipelines for structured and unstructured data across documents, FAQs, CRMs, and ERP systems.

RAG Architecture Setup

Implementing production-ready RAG pipelines connected with vector databases such as Pinecone, FAISS, Milvus, or Chroma to enable semantic search and retrieval.

Integrations & Tech Stack

Our Conversational AI & RAG solutions are built on a modular, open, and scalable technology architecture that adapts easily to any enterprise IT ecosystem. We integrate seamlessly with the best-of-breed LLM APIs, open-source models, and high-performance vector databases to deliver robust, production-ready systems

LLM Providers & Models

We work with leading models and APIs, including OpenAI (GPT-4, ChatGPT series) and Anthropic (Claude series) for cutting-edge conversational capabilities. We also leverage powerful open-source models from Hugging Face (like Llama and Mistral) for fine-tuning and domain-specific adaptation.

Development Frameworks & Orchestration

We use advanced orchestration frameworks like LangChain and LlamaIndex to build complex, agentic workflows, manage conversational flows, and ensure reliable RAG pipelines.

Top-Tier Vector Databases

Our expertise covers the leading vector databases required for high-speed semantic search. We commonly work with Pinecone, Milvus, Weaviate, Chroma, and FAISS, selecting the best option based on your scalability, security, and deployment needs.

MLOps & Observability

We ensure enterprise-grade reliability using tools like LangSmith for tracing and debugging, alongside robust CI/CD and monitoring workflows.

Proprietary Governance Layer

We use advanced orchestration frameworks like LangChain and LlamaIndex to build complex, agentic workflows, manage conversational flows, and ensure reliable RAG pipelines.

Tech Stack

OpenAI

Anthropic

Gemini

Hugging Face

Mistral AI

Our AI/ML Development Process

Maximize the possibilities of the newest AI/ML version. You can hire our AI/ML developers, who are competent in the technical and interactive abilities required to meet your project's objectives.

Discovery & Initial Planning

We begin by understanding your requirements and goals, ensuring a tailored approach.

Data Gathering & Cleaning

We collect and preprocess data to ensure accuracy and quality for model development.

Model Development and/or Training

Our AI/ML experts build scalable, high-performing models using advanced algorithms.

Testing & Validation

We rigorously test models using real-world data to ensure they meet your objectives.

Deployment

Our team implements the solution in a live environment, ensuring seamless integration.

Maintenance & Support

We offer ongoing support and maintenance to optimize and update your AI/ML solutions over time.

Building The Enterprise of The Future

Conversational AI & RAG represent more than just a technology shift; they mark a transformation in how knowledge flows within businesses. With scalable enterprise chatbots, semantic search systems, and knowledge bots powered by LLMs, companies can create a living, continuously learning interface that adapts with every interaction.

By bridging human intelligence with Retrieval-Augmented Generation frameworks and leveraging LangChain, vector databases, and MCP-secured deployments, your enterprise can move beyond automation toward intelligent decision enablement.

Our goal is simple: create AI-driven assistants that learn your business language, understand your users, and deliver measurable business outcomes. From fast POCs to production-ready RAG pipelines, every deployment is built for performance, compliance, and trust.

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FAQs for LLM and RAG Solutions

Model Context Protocol, or MCP, is a secure framework that governs how AI models interact with data, tools, and systems in enterprise environments. It ensures all agent actions are authorized, traceable, and compliant by enforcing role-based access, logging, and deterministic handovers between models and connectors.