Your users expect AI-powered intelligence. QuantPi.ai integrates large language models into your existing product with production-grade RAG pipelines, hallucination guardrails, cost optimization, and enterprise security. GPT-4, Claude, Llama, Mistral — we work with all of them.
Production LLM integration is engineering, not experimentation.
We map your product workflows to LLM capabilities. Which features benefit from language understanding? Where does generation add value? What are the accuracy and latency requirements?
Choose the right approach — prompt engineering, RAG, fine-tuning, or hybrid. Design the retrieval pipeline, model selection, fallback strategies, and cost architecture.
Implement the integration with comprehensive evaluation frameworks. Automated testing against human-annotated benchmarks. Red-teaming for safety. Latency and cost optimization.
Production rollout with real-time monitoring for accuracy, latency, cost, and safety. Continuous evaluation against golden datasets. Alert systems for quality degradation.
Retrieval-augmented generation that grounds LLM responses in your product data. Vector databases, hybrid search, re-ranking, and chunk optimization for accurate, hallucination-free answers.
Custom models trained on your domain data for consistent style, terminology, and accuracy. When RAG is not enough, fine-tuning delivers the precision your product demands.
Multi-layer verification: citation grounding, confidence scoring, fact-checking pipelines, and human-in-the-loop escalation. Your users never see a hallucinated response.
Model routing, response caching, prompt compression, and tiered model selection. Reduce LLM API costs by 40-60% without sacrificing quality.
Replace keyword search with AI-powered understanding. Users find what they mean, not just what they type. Works across documents, products, knowledge bases, and support tickets.
Multi-step AI agents that can research, analyze, draft, and act within your product. From simple chatbots to complex autonomous workflows with human oversight.
AI-powered search, smart assistants, content generation, report drafting, and workflow automation embedded directly into your SaaS product.
Product descriptions at scale, conversational commerce, intelligent customer support, review summarization, and personalized recommendations.
Contract analysis, legal research assistants, document summarization, clause extraction, and compliance checking powered by domain-specific LLMs.
AI tutoring systems, content generation, assessment creation, personalized learning paths, and intelligent feedback powered by curriculum-grounded RAG.
Clinical documentation assistants, patient communication, medical literature summarization, and symptom triage — all with medical-grade accuracy guardrails.
Financial report analysis, regulatory document processing, customer communication drafting, and market intelligence summarization.
It depends on your requirements. GPT-4 for maximum capability, Claude for long-context and safety, Llama for on-premise deployment, Mistral for cost-efficiency. We often use multiple models with intelligent routing.
Multi-layer approach: RAG grounding in verified data, citation requirements, confidence scoring, automated fact-checking, and human-in-the-loop for low-confidence responses. We achieve 94%+ factual accuracy in production.
We support both API-based and self-hosted models. For sensitive data, we deploy open-source models (Llama, Mistral) within your own infrastructure. Your data never leaves your environment.
Raw API costs can be significant at scale. Our optimization techniques — caching, prompt compression, model routing, and tiered selection — typically reduce costs by 40-60% while maintaining quality.
Yes. We design LLM integrations as modular services that connect to your existing architecture via APIs. Minimal changes to your codebase — maximum AI capability.
A basic chatbot or search integration: 2-4 weeks. A full RAG pipeline with guardrails: 6-8 weeks. Complex agentic workflows: 8-12 weeks. We move fast because we have done this 50+ times.
Book a demo and see how we integrate production-grade LLM capabilities — with the guardrails your users trust.