RAG Pipeline Development
Unlock Your Data with RAG-Powered AI Solutions
Build Retrieval-Augmented Generation pipelines that give AI access to your proprietary data. Our engineers design and deploy production-grade RAG systems that deliver accurate, grounded AI responses using your documents, databases, and knowledge bases.
Trusted by leading companies
What is RAG Development?
RAG (Retrieval-Augmented Generation) Development involves building systems that combine the reasoning power of large language models with your private, proprietary data to produce accurate, grounded AI responses. Our engineers design document processing pipelines, embedding strategies, vector store architectures, and retrieval systems that ensure your AI can access the right information at the right time — eliminating hallucinations and delivering trustworthy answers based on your organization's actual knowledge.
Flexible Engagement Models
Choose the engagement model that best fits your RAG project needs and budget
| Engagement Type | Proof of Concept 4-6 weeks | Full Development 8-12 weeks | Managed RAG Platform Ongoing support |
|---|---|---|---|
| Data assessment & strategy | |||
| Document processing pipeline | |||
| Production deployment | — | ||
| Multi-source data integration | — | ||
| Ongoing optimization & monitoring | — | — | |
| Dedicated support team | — | — |
Benefits of Rag Development Staff Augmentation from Jishu Labs
Software staff augmentation is a strategic approach to scaling your team with skilled professionals. It is a cost-effective solution that reduces expenses while enhancing team flexibility and operational efficiency. By leveraging a nearshore development team, businesses can quickly scale their teams and maintain high-quality standards, addressing recruitment challenges effectively.
Our 6-Step RAG Development Process
From data assessment to production deployment in as little as 6 weeks
Client Testimonials
Trusted by leading companies
The team delivered exceptional results, exceeding our expectations in both quality and timeline. Their expertise in AI development was evident throughout the project.
RAG Technology Stack
We leverage the latest retrieval and AI technologies to build production-grade RAG systems
Embedding Models
- •OpenAI Embeddings
- •Cohere Embed
- •Voyage AI
- •BGE & E5 Models
- •Sentence Transformers
Vector Databases
- •Pinecone
- •Weaviate
- •Chroma
- •Qdrant
- •pgvector
RAG Frameworks
- •LangChain
- •LlamaIndex
- •Haystack
- •Semantic Kernel
- •Unstructured.io
Large Language Models
- •Claude (Anthropic)
- •GPT-4 (OpenAI)
- •Llama (Meta)
- •Mistral
- •Gemini (Google)
Document Processing
- •Apache Tika
- •Unstructured
- •LlamaParse
- •Docling
- •Custom Parsers
Cloud Infrastructure
- •AWS Bedrock
- •Google Cloud AI
- •Azure OpenAI
- •Docker & Kubernetes
- •Terraform
Our RAG Development Team
Specialized engineers with deep expertise in building production-grade RAG systems
RAG Engineer
Designs and implements end-to-end retrieval-augmented generation pipelines including chunking, embedding, retrieval, and generation strategies
Data Engineer
Builds robust data ingestion pipelines, document processors, and automated data refresh systems for continuous knowledge updates
ML Engineer
Handles embedding model selection, fine-tuning, evaluation metrics, and optimization of retrieval and generation quality
Backend Developer
Builds the API layer, query processing services, and integration middleware that power the RAG system in production
DevOps Engineer
Manages vector database infrastructure, deployment pipelines, scaling, and monitoring for production RAG systems
AI Solutions Architect
Designs the overall system architecture, selects technologies, and ensures the RAG solution meets enterprise scalability and security requirements
A Few of Our Clients
Web Application Development. Designed and developed backend tooling.
Developed Generative AI Voice Assistant for Gaming. Built Standalone AI model (NLP)
Designed, Developed, and Deployed Automated Knowledge Discovery Engine
Backend Architectural Design, Data Engineering and Application Development
Application Development and Design. Deployment and Management.
Data Engineering. Custom Development. Computer Vision: Super Resolution
Designed and Developed Semantic Search Using GPT-2.0
Designed and Developed LiveOps and Customer Care Solution
Designed Developed AI Based Operational Management Platform
Build Automated Proposal Generation. Streamline RFP responses using Public and Internal Data
AI Driven Anomaly Detection
Designed, Developed and Deployed Private Social Media App
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