How Signals Works

Multi-model orchestration—including ensemble and mixture of experts approaches—meets strategic foresight. Our methodology combines cutting-edge AI with proven frameworks to deliver reliable strategic intelligence.

Our Core Methodology

Signals orchestrates multiple AI models in parallel to identify patterns, assess relevance, and generate actionable insights. Our four-stage process ensures comprehensive analysis while maintaining quality and reliability.

Stage 1
Ensemble Generation

AI models analyze your query simultaneously, each bringing unique perspectives and capabilities to ensure comprehensive coverage.

Stage 2
Deduplication

Advanced semantic analysis identifies and consolidates duplicate signals while preserving unique insights and calculating confidence scores.

Stage 3
Assessment

Each signal is evaluated for strategic relevance, potential impact, and actionability using specialized assessment frameworks.

Stage 4
Report

AI-powered synthesis creates comprehensive executive reports with category insights and strategic recommendations.

Stage 5

Interactive Visualization

Transform complex strategic data into intuitive, interactive radar visualizations designed specifically for foresight analysis and strategic decision-making.

Powered by Leading AI Models

We orchestrate the most advanced AI models available, each contributing unique strengths to ensure comprehensive and accurate analysis.

Anthropic
Claude Sonnet 4
Anthropic
OpenAI
GPT-4.1
OpenAI
Mistral
Mistral Medium 3
Mistral
Perplexity
Sonar Pro
Perplexity
DeepSeek
DeepSeek Chat V3
DeepSeek
Google
Gemini 2.5 Flash Preview
Google
MoonshotAI
Kimi K2
MoonshotAI
xAI
Grok 3
xAI
Meta
Llama 4 Maverick
Meta
Alibaba
Qwen Plus
Alibaba
Liquid
LFM 3B
Liquid
What is a Signal?
Understanding Signals

A signal is a noteworthy observation or data point that hints at a potential change, trend, or emerging pattern. In strategic foresight, signals are early indicators that can precede larger shifts—helping anticipate disruptions or opportunities. Signals are granular, contextual, and require interpretation to assess their relevance or impact.

What Makes Our Methodology Unique

Multi-Model Consensus

Instead of relying on a single AI model, we analyze consensus and disagreement across multiple models to identify the most reliable insights.

Semantic Deduplication

Advanced natural language processing identifies conceptually similar signals even when expressed differently, ensuring clean, actionable results.

Confidence Scoring

Each signal receives a confidence score based on frequency, consensus, and originality, helping prioritize the most reliable insights.

Source Grounding

Signals from grounding-capable models include source links for verification, while others undergo additional validation processes.

Rapid Processing

Parallel model execution and optimized processing pipelines deliver comprehensive analysis in minutes, not days or weeks.

Interactive Visualization

Purpose-built radar visualizations make complex foresight data accessible and actionable for strategic decision-making.

Experience Our Methodology

See our multi-model approach in action. Try a demo scan or explore our comprehensive methodology documentation.