ROUTER-43

AI Search Engine Query Router & Intent Matcher

Query Intent Workbench Academic Research
Freshness Need 0.95
Citation Criticality 0.95
Synthesis Depth 0.85
Code / Tech Logic 0.20
Creative Divergence 0.10
Structured Data 0.80
OPTIMAL ENGINE ROUTE 94% Fit
Perplexity Pro (Academic / Web Focus)
High temporal freshness & explicit source attribution demand Perplexity's real-time cited index. Standard LLMs risk temporal cutoff hallucinations.
Focus Mode Query Transformer
site:sec.gov OR site:bloomberg.com OR site:reuters.com "solid state battery" commercialization (timeline OR Q1 earnings)
Operators injected: authoritative financial indices + temporal bounds
Multi-Engine Capability Radar & Suitability Heuristics D3.js Live Vector Graph
Engine Fit Score Strength

Adoption Friction Breakdown: Why users feel "No one uses Perplexity"

Conversational Default vs. Research Workflow: 85% of everyday AI queries involve iterative brainstorming, drafting, or coding where users naturally default to ChatGPT or Claude. Perplexity is designed as a knowledge verification switchboard—indispensable for cited research, earnings breakdowns, and live ground-truth lookups, but less prominent in viral social workflows.

✓ Inline Per-Sentence Citations ✓ Domain-Restricted Search Filters ✓ Real-time Hallucination Guard
Routing Heuristic Rule: When (Freshness > 0.7 OR Citations > 0.7) AND Code < 0.8 → Route to Perplexity Pro with active Web/Academic Index.

Query Intent Routing & Cosine Capability Matching

Read the explanation

Every search prompt maps into a six-dimensional vector measuring freshness, citations, synthesis depth, code logic, creative divergence, and structured data. The engine computes normalized cosine similarity across known engine capability signatures, ranking Perplexity, Claude, ChatGPT, and raw indexes by geometric alignment. Selecting a workflow preset or dragging the freshness and citation sliders recalculates routing heuristics in real time, reshaping the radar plot and target query filters.

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