Our AI Technology Stack

At Predictive Tech Lab, we leverage the most advanced language models and frameworks to build intelligent, accurate, and reliable chatbot solutions. Our technology stack is carefully selected to ensure optimal performance, security, and scalability.

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Advanced Language Models

We integrate state-of-the-art large language models from leading providers including OpenAI, Anthropic, Google, and AWS. Each model is selected based on your specific use case requirements for optimal performance.

  • OpenAI GPT Series: Industry-leading comprehension and generation
  • Anthropic Claude: Enhanced safety and longer context windows
  • Google PaLM/Gemini: Multimodal capabilities and deep reasoning
  • AWS Titan: Cost-effective and scalable solutions
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LangChain Framework

Our RAG solutions are built on LangChain, the industry-standard framework for developing applications powered by language models. This enables sophisticated workflows and seamless integration.

  • Chain-based processing for complex queries
  • Memory management for context retention
  • Agent-based autonomous problem solving
  • Seamless tool and API integration
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Vector Databases

We utilize advanced vector databases to enable fast, semantic search across your documents and data. This ensures your chatbot finds the most relevant information every time.

  • Pinecone: Scalable, managed vector search
  • Weaviate: Open-source with advanced features
  • ChromaDB: Lightweight and efficient
  • Azure Cognitive Search: Enterprise-grade search
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Embedding Models

High-quality embeddings are crucial for semantic understanding. We use state-of-the-art embedding models to convert text into meaningful vector representations.

  • OpenAI text-embedding-3 models
  • Sentence-BERT for domain-specific tasks
  • Cohere embeddings for multilingual support
  • Custom fine-tuned embeddings

How RAG Technology Works

Retrieval-Augmented Generation combines the power of large language models with your proprietary data to deliver accurate, context-aware responses.

1

Document Ingestion

Your documents (PDFs, Word files, databases, APIs) are processed and converted into structured data.

2

Vectorization

Content is transformed into high-dimensional vectors using advanced embedding models for semantic search.

3

Semantic Retrieval

When a user asks a question, we find the most relevant chunks from your knowledge base.

4

Augmented Generation

The LLM generates accurate answers using retrieved context, always citing sources.

Integration & Customization

🔧 Custom Model Fine-Tuning

We can fine-tune language models on your specific domain data for enhanced performance and accuracy tailored to your industry.

🎯 Prompt Engineering

Expert prompt design ensures your chatbot provides consistent, on-brand responses that align with your business objectives.

🔄 Continuous Learning

Our systems improve over time through feedback loops, user interactions, and regular model updates.

🛡️ Safety & Compliance

Built-in content filtering, PII detection, and compliance guardrails ensure responsible AI usage.

📈 Performance Monitoring

Real-time analytics track accuracy, response times, user satisfaction, and system health.

🌍 Multilingual Support

Deploy chatbots in 100+ languages with native-level comprehension and generation capabilities.

Ready to Leverage Advanced AI?

Let's discuss how our LLM technology can transform your business