Retrieval-Augmented Generation for Enterprises
Is it still a challenge for your organization to find the right information in large document repositories while AI tools deliver generic or hallucinated answers?
Our Retrieval-Augmented Generation platform combines advanced AI with your business data to provide accurate, secure, and context-aware responses. Book a demo to see how your documents can become an intelligent AI assistant.
Why Retrieval-Augmented Generation Is Essential for Modern Enterprises
Precision
Answers only from your verified documents. No hallucinations. No liability risks
Advantage
AI that understands your products, your customers, your market position
Control
Your data stays private. Never used to train public models. Complete compliance
Enterprise-Grade Retrieval-Augmented Generation Infrastructure That Just Works
We handle the complexity of connecting your data to AI. Simply upload your documents, and our platform takes care of parsing, chunking, indexing, and retrieval—so your AI delivers accurate, context-aware answers instantly.
Best-in-Class Indexing and Retrieval
Search, index, and retrieve data in milliseconds. Built for speed, accuracy, and enterprise scale.
Chunking – Divides documents into optimal chunks that maintain semantic coherence, improving accuracy while reducing noise.
Parsing – Automatic conversion of PDFs, Office files, web pages, and unstructured data into AI-ready formats without manual configuration.
Indexing – Builds vector embeddings, keyword indexes, and metadata stores for fast, comprehensive search.
Extraction – Identifies structure, entities, metadata, and relationships within your content, enabling precise filtering and context-aware retrieval.
Retrieval – Combines multi-index search with intelligent re-ranking to deliver the most relevant context to your LLM.
Multimodal
Designed to process any content type, our multimodal ingest pipeline handles text, PDFs, images, audio, video, tables, and more.
Audio and video Automatic transcription with intelligent chunking and retrieval, including timestamps and streaming playback for spoken and visual content.
PDFs Handles complex PDFs with ease, extracting text, tables, charts, and images from documents of any size.
Structured Data Ingests databases, spreadsheets, and JSON, delivering grounded, context-rich results for any LLM through multi-index retrieval.
Text Processes plaintext and rich formats like DOCX and HTML, unstructured content becomes searchable, ready for parsing, chunking, and retrieval.
Presentations Extracts content from PowerPoints and Google Slides, including speaker notes, slide text, and embedded visuals for complete retrieval.
Application Ready
Pre-built features and integrations that accelerate your AI application development.
Data Source Connectors Native integrations with enterprise platforms like Google Workspace, Microsoft 365, Confluence, Notion, and cloud storage providers.
User-Managed Connections Allow your customers to securely connect their own data sources through embedded authentication flows.
Developer APIs Complete REST API coverage for document management, search configuration, and retrieval operations.
Client Libraries Official SDKs for major programming languages with built-in error handling, retry logic, and type safety.
Multi-Tenant Architecture Logically separate customer data into isolated partitions for secure multi-tenancy, focused retrieval, and enhanced data privacy.
Event Streaming Real-time webhooks for monitoring document ingestion, updates, and system events across your application.
AI Chatbot Application
Instantly get accurate, source-backed answers from your company’s docs, wikis, and tools, all in one place.
Accurate Answers Retrieval-powered responses grounded in your actual documents, reducing hallucinations and incorrect information.
Automatic Citations Every response links back to source documents, enabling quick verification and deeper exploration.
Secure & Private Role-based access ensures users only receive answers from documents they’re authorized to view.
Retrieval-Augmented Generation Engineered for Accuracy and Trust
Built for enterprises by AI engineers to help you scale AI securely, accurately, and efficiently.
Your data. Your control. Always.
Data Privacy
Total control over your data. Zero retention policies, private deployment, and customer-managed encryption—your security rules, not ours.
Compliance Ready
Enterprise compliance, built-in. SOC 2, GDPR, HIPAA certified with automatic audit logging—check the compliance box without extra work.
Access Control
Granular security, zero friction. SSO, RBAC, and document permissions integrate with your existing identity systems seamlessly.
Integrate With Your Existing Stack in Minutes.
Cenango connects to your data sources and AI models without disrupting your workflow.
FAQs
What is Retrieval Augmented Generation?
Retrieval Augmented Generation (RAG) is smart AI that uses your own documents to answer questions. It searches your files, finds the right information, and gives you accurate answers. Think of it as a super-smart assistant that knows everything in your company files.
Is ChatGPT a Retrieval Augmented Generation (RAG)?
No, ChatGPT is not a Retrieval Augmented Generation system. ChatGPT only knows general information from its training. It cannot access your company documents. Retrieval Augmented Generation systems like Cenango read your specific files and give answers based on your real data. This makes RAG much better for business use.
What is the difference between Retrieval Augmented Generation and LLM?
An LLM (Large Language Model) is the AI brain. Retrieval Augmented Generation is the complete system. Retrieval Augmented Generation combines an LLM with your documents. The LLM understands language. Retrieval Augmented Generation adds your company knowledge. This gives you accurate, trustworthy answers from your own information.
What is an example of Retrieval Augmented Generation?
Here’s a simple example. An employee asks: “What is our vacation policy?” RAG searches your HR documents, finds the policy, and answers: “You get 15 days per year, as stated in the Employee Handbook.” It even shows the source document. Fast, accurate, and helpful!
How does Retrieval-Augmented Generation work?
Retrieval Augmented Generation works in three simple steps. First, it reads and organizes all your documents. Second, when you ask a question, it searches for relevant information. Third, it creates a clear answer using what it found. Every answer includes links to the original documents for proof.
Why use Retrieval-Augmented Generation?
Retrieval Augmented Generation saves time and improves accuracy. Your team finds answers in seconds, not hours. Customers get help faster. New employees learn quickly. Everyone gets the same correct information. Plus, you always know where the answer came from because RAG shows its sources.
What Google Cloud products and services are related to Retrieval-Augmented Generation?
Google Cloud offers Vertex AI Search for Retrieval Augmented Generation solutions. It also provides Cloud Storage for documents, BigQuery for data, and Gemini AI models. These tools work together to build RAG systems. Cenango can integrate with Google Cloud to give you powerful search capabilities.
How do we know the Retrieval-Augmented Generation is right for my business?
Retrieval Augmented Generation is right for you if your team spends time searching for information. If you have lots of documents, policies, or manuals, It helps. If customers ask the same questions repeatedly, RAG answers them. If new employees need training, Retrieval Augmented Generation speeds it up. Most businesses benefit greatly.
Is Retrieval-Augmented Generation a framework or platform?
Retrieval Augmented Generation can be both. The concept is a framework – a way of building AI systems. Cenango is a complete platform. We handle all the technical work. You just connect your documents and start asking questions. Our platform makes RAG simple and ready to use right away.
How long does a Retrieval-Augmented Generation solution need to be implemented?
Most businesses go live in two to four weeks. Small projects can start in one week. Larger companies with many documents might need six weeks. The timeline depends on how many files you have and which systems we need to connect. We give you a clear schedule from day one.
What should I check before implementing Retrieval-Augmented Generation for my business?
Check these five things first. One: What documents do you have? Two: Where are they stored? Three: Who needs access? Four: What questions do people ask most? Five: What is your budget? Knowing these helps us create the perfect solution for you. We guide you through everything.
How much does a Retrieval-Augmented Generation platform cost?
Costs vary based on your needs. Pricing depends on users, documents, and features. We offer a free 14-day trial. Contact us for a custom quote that fits your budget perfectly.
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