CRAZY UNICORNSRAG Development & Implementation
We build retrieval-augmented generation systems that connect LLMs to your data with precision, evaluation, and production-grade reliability.
Production-ready RAG systems
We specialize in designing and building robust Retrieval-Augmented Generation (RAG) systems that connect your proprietary data to the power of Large Language Models.
Our focus is on creating reliable, scalable, and secure solutions that move beyond simple demos to deliver measurable business value in production environments.
Common RAG use cases
Internal Knowledge Base Search
Enable employees to ask natural language questions and get precise answers from internal documentation, wikis, and databases.
Customer Support Automation
Power chatbots and agent-assist tools with access to your full knowledge base, providing accurate, context-aware answers.
Compliance & Document Analysis
Automate the process of querying and verifying information across large volumes of regulatory documents, contracts, and reports.
Product & Feature Discovery
Help users find relevant products or features by understanding their needs expressed in natural language.
Data-driven Decision Support
Create interfaces where analysts can query complex structured and unstructured datasets to get synthesized insights.
Our RAG implementation process
Data Source & Pipeline Analysis
We map your data ecosystem and build robust pipelines for ingesting and pre-processing structured and unstructured data.
Chunking & Embedding Strategy
We design and test optimal content chunking and embedding models to ensure relevant context is captured for the retriever.
Retrieval Model Implementation
We implement and tune retrieval systems (e.g., vector search, hybrid search) to fetch the most relevant information with high precision.
Generation & Prompt Engineering
We engineer effective prompts that guide the LLM in synthesizing accurate, coherent answers based on the retrieved context.
Evaluation & Deployment
We establish rigorous evaluation frameworks to measure performance and deploy the system into a scalable, monitored production environment.
RAG Architecture & Technology
Our RAG architectures are built for performance and reliability. We utilize best-in-class vector databases, retrieval algorithms, and orchestration frameworks.
We design for scalability, security, and observability, ensuring your RAG system can handle enterprise demands and is easy to maintain and improve over time.
Why partner with us for RAG
We build RAG systems that work in the real world.
Build your production RAG system
Let's discuss how a well-architected RAG solution can unlock the value of your data. We offer clear technical guidance and a path to production.