Retrieval-Augmented Generation Services

TPSReport

Your company's data is your greatest asset. We use RAG to ground powerful generative AI in your secure, internal knowledge base. This unlocks instant, accurate answers from your own data, eliminating AI "hallucinations" and ensuring your proprietary information remains private.

Transform your internal documents, databases, and knowledge repositories into intelligent, conversational interfaces that provide accurate, contextual responses while maintaining complete data control.

The RAG Advantage

Eliminate Hallucinations

Ground AI responses in your actual data, not training data. Every answer is backed by specific sources from your knowledge base.

Keep Data Private

Your proprietary information never leaves your infrastructure. Complete control over data access and usage.

Always Current

Unlike trained models, RAG systems stay current with your latest data, documents, and knowledge updates.

Source Attribution

Every response includes citations and references, allowing users to verify information and explore further.

Cost Effective

Avoid expensive model retraining. Add new knowledge by simply updating your document repository.

Fine-Grained Control

Control what information is accessible to different users, teams, or use cases through sophisticated access controls.

How RAG Works

1

Document Ingestion

We process your documents, databases, and knowledge sources, extracting and structuring information for optimal retrieval.

PDFs, Word docs, databases, APIs, wikis, and more
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2

Semantic Indexing

Content is transformed into vector embeddings, creating a semantic understanding that goes beyond keyword matching.

Advanced embedding models, chunk optimization, metadata preservation
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3

Intelligent Retrieval

When users ask questions, the system finds the most relevant information using semantic similarity and contextual understanding.

Hybrid search, reranking, context optimization
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4

Augmented Generation

The language model generates responses using the retrieved context, ensuring accuracy and providing source citations.

Context-aware generation, source attribution, factual grounding

Common Use Cases

Customer Support Knowledge Base

Transform support documentation into an intelligent assistant that provides instant, accurate responses to customer inquiries with source citations.

Internal Employee Q&A

Give employees instant access to company policies, procedures, and institutional knowledge through conversational interfaces.

Research & Due Diligence

Quickly find relevant information across large document collections, perfect for legal research, financial analysis, or technical documentation.

Product Documentation

Enable users to ask natural language questions about complex products, APIs, or technical systems and get accurate, contextual answers.

Regulatory Compliance

Ensure teams can quickly find and understand relevant regulations, policies, and compliance requirements from your knowledge base.

Training & Onboarding

Accelerate employee training by providing intelligent access to training materials, best practices, and institutional knowledge.

Our RAG Technology Stack

Vector Databases

  • Pinecone
  • Weaviate
  • Chroma
  • Qdrant

Embedding Models

  • OpenAI Embeddings
  • Sentence Transformers
  • Cohere Embeddings
  • Custom fine-tuned models

Document Processing

  • LangChain
  • LlamaIndex
  • Unstructured.io
  • Custom parsers

Search & Retrieval

  • Elasticsearch
  • Hybrid search
  • Reranking models
  • Query expansion

Ready to unlock your knowledge base?

Let's discuss how RAG can transform your data into intelligent, conversational interfaces.

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