RAG as a service RAG as a service

RAG as a service

Transform your LLMs from general-purpose content generators into reliable, domain-savvy systems with our RAG-as-a-service offering. Break through the limits of generic AI!
RAG as a service

Why is RAG development a must-have?

What’s holding back enterprise LLM adoption? Inaccuracies, outdated data, and lack of business context. RAG fixes all three. Our retrieval-augmented generation services will help you to:

Fix hallucination issues & gain user trust

LLMs often generate convincing yet incorrect answers—a major liability for enterprises. RAG eliminates this risk by grounding responses in real, verifiable data.

Reduce reliance on outdated information

Most LLMs are trained on static, outdated data. RAG enables live data access via APIs, internal databases, or the web, ensuring that your AI applications stay relevant and responsive.

Gain access to specialized domain knowledge

LLMs don’t natively understand your industry-specific jargon, policies, or proprietary content. With RAG, you can inject your internal documents into the model’s context.

ITRex RAG development services: your fast track to smart AI

We turn your data silos into strategic assets with our AI-powered enterprise RAG as a service solutions—delivering precise answers, not just search results. Here is what we offer:

RAG consultation & support

As part of our retrieval-augmented generation services, we provide strategic consultation to help enterprises evaluate their AI readiness, identify high-value use cases, and chart a roadmap for successful adoption. Our experts ensure your organization is aligned from infrastructure to impact.

Custom retrieval-augmented generation development

We deliver tailored RAG development services that integrate seamlessly into your data ecosystem. From building retrieval pipelines to prompt optimization and LLM integration, our custom RAG solutions are built to face real-world enterprise challenges.

Information retrieval system development

Our RAG-as-a-service capabilities include building intelligent retrieval systems that deliver fast, accurate access to business-critical information. Using semantic, hybrid, and graph-based search, we enable real-time, context-rich discovery across large, dynamic content sources.

Multimodal RAG development

We enable you to expand your AI potential with RAG solutions that support text, audio, image, and video content. We implement multimodal RAG using advanced embeddings to enable diverse, media-rich user experiences for internal and customer-facing applications.

RAG-based knowledge management system development

ITRex builds advanced knowledge systems powered by RAG solutions that consolidate fragmented enterprise data into centralized, domain-specific repositories. These systems grant easy access to your organizational knowledge and drive informed decision-making.

Data preparation & strategy crafting

A strong data foundation is essential for successful RAG as a service delivery. Our data consultants design ingestion pipelines, structure data for efficient retrieval, and define data management strategies to ensure your RAG system is reliable, scalable, and compliant.

Our RAG solutions are tailored to your industry

RAG isn't just a technical innovation—it's a strategic advantage across sectors that deal with large volumes of complex, evolving information. Here is how our RAG development services can transform your domain:

RAG solutions help medical facilities enhance clinical decision-making by retrieving the latest research, treatment protocols, and patient-specific insights in real time. From diagnosis to discharge, RAG as a service enables providers to access accurate information instantly while meeting strict compliance standards like HIPAA.

In this sector, RAG development is revolutionizing compliance, risk management, and fraud detection. Our feature-rich RAG solutions retrieve and contextualize regulatory texts, analyze transaction data for suspicious patterns, and automate reporting to reduce audit workloads and increase efficiency.

Manufacturers can use our RAG development services to build AI assistants that guide technicians through maintenance and troubleshooting, pulling insights from equipment manuals, repair logs, and sensor data. RAG also unifies data across the supply chain to improve inventory visibility and predict delays.

Legal

Legal teams use our RAG solutions to streamline time-intensive tasks like case research, document analysis, and contract review. By surfacing relevant precedents, summarizing legal documents, and generating context-aware insights, RAG helps firms accelerate case preparation and ensure no critical detail is missed.

RAG transforms customer experiences through fast, accurate, and personalized support. Our RAG-as-a-service offering integrates with knowledge bases, product catalogs, and CRM systems to resolve customer queries, guide purchase decisions, and deliver tailored recommendations in real time.

Educational institutions can use ITRex RAG solutions to create intelligent tutoring systems, automate curriculum support, and enhance content discovery. From answering student queries to helping instructors organize materials, our RAG development services support more personalized, scalable learning experiences.

End-to-end RAG development, the ITRex way

At ITRex, we follow a structured approach to delivering high-performance RAG solutions. Each phase is designed to maximize business value. Here is our process of developing a custom RAG application:

Discovery & strategic planning

  • Initial consultation
    Assessing your goals and identifying high-value use cases where RAG can deliver measurable ROI.
  • AI readiness assessment
    Evaluating your data, tech stack, and organizational maturity to ensure RAG implementation readiness.
  • Strategic roadmap development
    Crafting a clear, phased plan tailored to your needs. It covers tech selection, timeline, and success metrics.

RAG solution design & development

  • Data preparation and pipeline design
    Building data pipelines that clean, chunk, and embed diverse content into optimized vector databases.
  • Advanced retrieval mechanism implementation
    Deploying semantic, hybrid, and re-ranking methods to retrieve only the most relevant information.
  • LLM integration and prompt engineering
    Integrating your LLMs with the retrieval system and fine-tuning prompts for accurate, grounded, and business-aligned responses. We work with AWS Bedrock, Anthropic Claude API with MCP, Azure OpenAI, Google Gemini, and Cohere Command models, as well as self-hosted open-source alternatives.
  • Solution development
    Developing a custom RAG system that seamlessly fits into your existing enterprise applications. These solutions range from microservices architectures to serverless implementations using cloud platforms or on-premises deployment.

RAG system deployment & MLOps

  • Scalable infrastructure design
    Architecting cloud or on-premises systems that handle large data and high traffic with low latency. We utilize AWS ECS/EKS, Azure Container Services, Google Cloud Run, and Kubernetes orchestration with auto-scaling capabilities and caching layers.
  • Robust security, compliance, and governance
    Embedding enterprise-grade security, privacy controls, and regulatory compliance from day one. Implementation includes VPC isolation, encryption with AWS KMS/Azure Key Vault, OAuth integration, and compliance frameworks (GDPR, HIPAA, SOC 2).
  • Full system integration
    Ensuring your RAG solution integrates smoothly with current tools, systems, and workflows. We provide REST/GraphQL APIs, enterprise connectors, and Anthropic MCP integration for standardized tool connectivity.

Optimization & continuous support

  • Performance monitoring and evaluation
    Tracking metrics like response quality, groundedness, and hallucinations to ensure long-term value.
  • Self-correction
    Incorporating adaptive feedback loops to help your RAG system automatically improve itself over time.
  • Knowledge transfer and training
    Empowering your teams with training and documentation to manage and improve the solution internally.
  • Future-proofing and innovation
    Continuously integrating emerging RAG trends, such as graph RAG, multimodal AI, agentic RAG frameworks, and real-time streaming capabilities to keep your solution at the forefront of innovation.

What are the main benefits of using RAG for businesses?

RAG doesn’t just enhance LLMs. It transforms them into practical, trusted tools for real-world business impact. Our RAG development services bring this strategic business value for enterprises:
Enhanced accuracy and reliability
RAG reduces hallucinations by up to 90% by grounding AI responses in verifiable sources, increasing trust and enabling enterprise-wide adoption.
Real-time access to relevant information
Unlike static LLMs, RAG systems pull data from live databases and up-to-date sources, ensuring decisions are based on the latest facts, trends, and customer inputs.
Cost-effectiveness compared to other methods like LLM fine-tuning
RAG solutions introduce new data without expensive retraining, offering a low-maintenance way to keep AI systems current.
Unification of scattered organizational knowledge
RAG turns fragmented, siloed data into a searchable knowledge base that is accessible in natural language. This saves time and enables cross-team alignment.
Accelerated decision-making
By delivering fast, relevant insights from across the organization, RAG helps teams act quicker and more confidently—shortening decision cycles and increasing productivity.

ITRex: your partner for end-to-end RAG solution implementation

We don’t just build RAG systems—we engineer enterprise-grade AI solutions that are innovative, reliable, and aligned with your business goals. If you partner with ITRex, here’s what you get:
Deep technical expertise in generative AI. Our team masters cutting-edge approaches like graph RAG, multimodal RAG, and self-correcting systems, enabling us to solve even the most complex retrieval and reasoning problems. We also have an innovative R&D unit for the most daunting challenges.
Full-lifecycle AI partnership. From initial readiness assessment to scalable deployment and ongoing optimization, we support you at every stage, ensuring sustainable value and long-term success.
Lasting business impact. Our RAG development process is designed to reduce hallucinations, enhance transparency, and deliver measurable gains in efficiency, decision-making speed, and cost savings.
Proven success across regulated industries. With deep domain experience in heavily regulated sectors like healthcare, we offer RAG development services that meet strict compliance requirements while delivering high-impact results.

Our expertise across leading AI models

FAQs

How do I choose the right RAG as a service provider?

Look for a partner with proven expertise in RAG development, including advanced techniques like graph RAG or multimodal RAG. Prioritize providers offering on-demand RAG application development tailored to your industry and end-to-end support, just like ITRex is doing.

How much does RAG as a service cost?

The cost of RAG as a service depends on project complexity, data infrastructure, integration needs, and performance requirements. While it’s more cost-effective than full model fine-tuning, pricing typically ranges from $25,000 to $35,000 for MVPs.

Looking for a precise estimation? Book a call with our experts.

You can also find more information on the topic in our guide about calculating the cost of generative AI.

What are the typical use cases for RAG in marketing?

RAG powers real-time campaign optimization, generates hyper-personalized content, unifies customer insights, and automates responses. By grounding outputs in trusted, current data, it ensures accuracy and relevance in customer-facing communications.

How can I hire experienced RAG developers?

Work with a consulting firm offering RAG as a service, such as ITRex, or hire engineers with strong NLP, ML, and MLOps skills. Look specifically for RAG development experience, especially in areas like vector databases, data pipelines, and retrieval strategies.

Can RAG be integrated into existing enterprise systems?

Yes. RAG solutions are modular and can integrate seamlessly with your CRM, data warehouses, CMS, and other enterprise tools. With proper APIs and orchestration layers, RAG development can enhance your tech stack without major disruption.