Why Valyu
Understanding Valyu’s architecture, intended use cases, and design principles
Valyu is built on a fundamental belief: AI systems need access to comprehensive, authoritative knowledge to deliver factual, reliable outputs. It is designed to return the most contextually relevant information to the user’s query. This page explains our design decisions and what Valyu excels at.
Core Design Principles
1. AI-Native Architecture
Valyu is engineered from the ground up for AI agents and LLMs, not adapted from traditional search engines.
What this means:
- Semantic understanding over keyword matching
- Structured JSON responses optimized for LLM consumption
- Embedding-powered retrieval that understands context and intent
- RAG-optimized result formatting with citations and metadata
Why it matters: Traditional search APIs return links designed for human browsing. Valyu returns structured agent-ready data that reduces hallucinations and improves factual grounding in AI responses.
2. Comprehensive Search Index
Valyu unifies multiple authoritative data sources into a single search interface.
Our knowledge sources:
- Real-time web search for current events and trending topics
- Academic papers and journals for research-backed insights
- Books and literary content for comprehensive domain knowledge
- Financial market data for real-time economic information
- Proprietary datasets for specialized industry knowledge
Design rationale: AI agents need diverse, authoritative sources to provide complete answers. Rather than forcing developers to integrate multiple APIs, Valyu provides one comprehensive retrieval layer that spans the entire knowledge spectrum. It identifies user intent, searches for and returns the most relevant content.
3. Transparent Cost Control
Every search operation has predictable, granular pricing with developer-controlled limits.
Cost optimization features:
- Pay-per-use CPM pricing - no subscription overhead
- Max price controls - set spending limits per query
- Relevance thresholds - filter low-quality results automatically
- Source-specific pricing - premium sources cost more, but you choose when to use them
Philosophy: Developers should have complete control over their search costs without sacrificing result quality. Valyu’s transparent pricing model lets you optimize for your specific use case and budget.
What Valyu Is Designed For
✅ Ideal Use Cases
Retrieval-Augmented Generation (RAG)
- Grounding LLM responses with authoritative sources
- Reducing hallucinations in AI-generated content
- Providing citations and source attribution
AI Research Assistants
- Academic literature review and synthesis
- Cross-referencing multiple authoritative sources
- Finding recent developments in specific research domains
Knowledge-Heavy Chatbots
- Educational assistants requiring factual accuracy
- Professional services bots (legal, medical, financial)
Real-Time Information Retrieval
- News and current events integration
- Market data for financial applications
- Live data feeds for time-sensitive decisions
Specialized Domain Search
- Academic research across multiple disciplines
- Financial analysis requiring market data
- Technical documentation and implementation guides
Check out our data coverage page for data coverage across domains and Prompting Guide for best practices on how to use Valyu effectively.
What Valyu Is NOT Designed For
❌ Suboptimal Use Cases
A Direct Search Engine
- Users querying the Valyu API directly (not through an LLM tool call)
Real-Time Social Media Monitoring
- Twitter/X trending topics
- Social media sentiment analysis
- Viral content tracking
E-commerce Product Search
- Shopping comparisons and price tracking
- Product reviews and ratings
- Inventory and availability checking
Local Business Information
- Restaurant recommendations and reviews
- Local service provider listings
- Geographic and location-based queries
Creative Content Generation
- Image generation prompts
- Creative writing inspiration
- Entertainment recommendations
Integration Philosophy
Build your workflows on top Valyu
Core philosophy: Rather than trying to solve every agentic search use case, Valyu provides precise, comprehensive search capabilities that developers can compose into domain-specific workflows tailored to their exact needs.
Design Evolution
Valyu’s architecture continues evolving based on developer feedback and AI advancement:
Current focus areas:
- Better search precision - Especially for fuzzy queries and exact document matching
- General Agnetic Search - An API framework that can be used to build your own search workflows
- Multimodal search - Expanding beyond text to images and documents
- Custom source integration - Private data connectivity
- Advanced filtering - More granular result controls
If you have any feedback, please reach out to us at: contact@valyu.network
Getting Started with Valyu
Ready to integrate comprehensive search into your AI system?