An AI Knowledge Base That Learns and Improves Itself
Harness the power of pgvector and Retrieval-Augmented Generation (RAG) to instantly answer customer queries. Indexu automatically identifies knowledge gaps and crafts new articles to keep your answers sharp.
How Our RAG Pipeline Works
From raw data to perfectly grounded answers in milliseconds.
Document Ingestion
Web crawler, API, and article sync
Vector Embedding
pgvector dense HNSW storage
Hybrid Search (RRF)
Cosine similarity + BM25
Grounded Response
Accurate, hallucination-free AI
Flawless Accuracy with Hybrid Search
Don't rely on keyword matching alone. Indexu combines semantic context with exact text matching to surface the absolute best answers for your customers.
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Reciprocal Rank Fusion (RRF) intelligently merges dense cosine similarity scoring and sparse trigram BM25 keywords.
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HyDE Query Expansion hypothetical document embeddings bridge the gap between how customers ask and how your docs are written.
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PostgreSQL pgvector enterprise-grade HNSW indexing ensures high-speed, scalable vector storage right in your database.
Identify What Customers Can't Find
Stop guessing what documentation to write next. The AI Knowledge Gap Radar constantly analyzes unanswered search queries and support tickets.
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Semantic Clustering groups variations of the same unanswered question into actionable insights.
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1-Click AI Generation instantly generate a draft article tailored to answer the specific knowledge gap.
Complete Lifecycle & Analytics
Manage your documentation easily with our built-in WYSIWYG editor. Keep your content organized across multiple brands and track exact deflection rates.
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Helpfulness Voting customers vote on article helpfulness; negative votes flag content for review.
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AI Article Generation stuck on a topic? Generate a structured draft from a title or turn resolved tickets into articles.
Everything You Need for Enterprise RAG
Build an intelligent knowledge base that reduces support volume.
Web Crawler
Asynchronously index your existing public documentation, external wikis, or product manuals. Sitemap-first, robots.txt compliant, with scheduled re-crawls, per-workspace domain allowlists, and per-plan page budgets.
Multi-Model AI
Choose your engine: OpenAI, OpenRouter, DeepSeek, Qwen, Google Vertex AI, or AWS Bedrock, with dynamic model discovery per provider.
Search Deflection Metrics
Measure success by tracking exactly how many support tickets were prevented when customers found answers through the AI Knowledge Base.
Resolved Ticket Flywheel
Automatically distill complex, successfully resolved support tickets into new draft knowledge base articles to prevent similar future inquiries.
Multilingual Support
Store vector embeddings and serve answers dynamically across multiple languages, breaking down barriers for global customer bases.
Category Management
Organize knowledge with deep category hierarchies. Control visibility settings and restrict sensitive internal documents to agents only.
Hybrid Rank Fusion
Query Expansion
Content Source Types
AI Draft Articles
Ready to build a knowledge base that gets smarter every day?
Stop managing documents manually. Let AI find the gaps and draft the articles your customers actually need.