The Challenge: Hallucinations and Slow Ingestion in Enterprise AI
Enterprise customer support and technical teams waste hundreds of hours manually looking up policies, user manuals, and technical blueprints. DBTalker required a turnkey RAG (Retrieval-Augmented Generation) platform where non-technical business owners could upload complex 200+ page PDF manuals and embed an accurate, hallucination-free chatbot on their websites in minutes.
The Technical Solution: Hybrid Semantic Search & Streaming Next.js UI
InfoCaptia architected an enterprise-grade AI pipeline combining dense vector embeddings with sparse keyword search to achieve unmatched retrieval accuracy:
- Recursive Semantic Chunking: Documents are cleaned, tokenized, and embedded via text-embedding-3-small into PostgreSQL (pgvector) with HNSW indexes for sub-50ms similarity matching.
- Anti-Hallucination Guardrails: Prompts enforce strict source attribution. Every AI response includes clickable footnote citations linking back to exact page numbers in the source document.
- Streamed Conversational Frontend: Next.js Server-Sent Events (SSE) render instant token streaming at 60fps, providing instantaneous feedback to end users.
Results & Impact
- 70% Customer Inquiries Resolved Autonomously: Enterprise clients eliminated repetitive level-1 support tickets.
- Sub-800ms Time-to-First-Token: Optimized streaming pipelines ensure prompt answers even on complex legal and compliance queries.
- Delivered in 6 Weeks: Full multi-tenant SaaS architecture shipped from concept to live production ahead of schedule.