Semantic Search Across All Signals. Conviction Scores from Multi-Agent Synthesis.
Search across every signal, filing, and policy document with natural language. The AI synthesizes outputs from all five agents into conviction scores you can act on.
All five AI agents continuously generate signals from filings, insider trades, institutional holdings, policy changes, and options flow. Each signal is indexed for semantic search.
Search across all signals and source documents using natural language. Ask questions like "which energy companies have increasing insider buying and bullish policy signals?" and get instant, relevant results.
The Synthesis Engine combines individual agent signals, weighing agreement and disagreement across agents to produce conviction scores. When Policy, Fundamentals, and Insider agents all agree, conviction is highest.
Every conviction signal is tracked over 7-day, 30-day, and 90-day windows. Review historical accuracy to understand which signal combinations produce the best outcomes.
Semantic search understands meaning, not just keywords. Ask "which companies face regulatory headwinds in the semiconductor sector?" and the AI finds relevant policy signals, filing risk factors, and analyst sentiment — even if those exact words do not appear in the documents.
Conviction scores range from -100 (strong bearish) to +100 (strong bullish). They are generated by the Synthesis Engine which combines signals from all five agents, weighting by signal strength, recency, and inter-agent agreement. Multi-agent consensus significantly boosts conviction.
The AI can analyze any document in the SignalEdge system: SEC filings (10-K, 10-Q, 8-K), Federal Register publications, congressional bills, earnings call transcripts, and Form 4 insider transaction patterns.
Pro subscribers receive a generous monthly allocation of AI credits. Semantic search, document analysis, and question answering each consume credits. Credit usage is displayed before each operation so there are no surprises.
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