How Our AI System Works

Radical transparency into how we analyze companies and generate investment assessments.

Our AI Doesn't Predict — It Synthesizes

We combine multiple data sources and AI agents to help you understand a company's situation. The goal is to surface insights you might miss, not to tell you what will happen.

Where We Get Our Data

Our system ingests data from multiple sources to build a complete picture of each company.

Company Reports

Quarterly and annual filings, earnings releases, and investor presentations.

News & Events

Press releases, regulatory announcements, and market news from trusted sources.

Market Data

Real-time prices, trading volumes, analyst estimates, and technical indicators.

Macro Indicators

Interest rates, commodity prices, currency movements, and economic indicators.

The Two-Layer Architecture

Our AI works in two stages: first, specialized "domain experts" analyze specific data types. Then, an "investment team" synthesizes everything into a coherent assessment.

Data Sources
Reports
News
Market
Macro
Layer 1: Domain Synthesis
Qualitative
Quantitative
News Synthesis
Macro Synthesis
Weekly Intel
Sector Analysis
Layer 2: Investment Committee
Sentiment
Risk/Opportunity
Data Quality
Reconciliation
Charting
Orchestrator
Final Investment Assessment

Layer 1: The Domain Experts

Think of Layer 1 as organizing all the puzzle pieces before solving the puzzle. Each agent focuses on a specific type of analysis.

AgentWhat It AnalyzesWhen It Runs
Qualitative
Business model, competitive position, management quality, strategic risksWhen a new report is downloaded
Quantitative
Financial statements, KPIs, peer comparisons, valuation metricsWhen new period data is available
News Synthesis
Daily market news and 4-day aggregated trendsDaily and every 4 days
Macro Synthesis
Interest rates, commodities, currency, economic indicatorsWeekly
Weekly Intel
Rolling window of company-specific eventsWhen ≥3 events accumulate in 7 days
Sector Analysis
Industry-wide trends using advanced taxonomyPeriodically

The Decoupled Trigger System

Why "decoupled"? Traditional systems wait for all data to be ready before analyzing. Our system lets different types of analysis run independently, so you get insights faster.

Foundational Triggers

Standard Procedure
New Report / Period Data

Deep, comprehensive analysis of the entire business and financial state.

Qualitative & Quantitative Synthesis

Incremental Triggers

Event-Driven
Event Accumulation (≥3) / Schedule

Rapid updates to layer in news, macro changes, and tactical events.

News, Macro & Weekly Intelligence

📄 Foundational Triggers

Triggered by new reports or data availability.

  • Create deep, comprehensive analysis
  • Take longer but produce complete picture
  • Form the backbone of assessments

⚡ Incremental Triggers

Triggered by event accumulation or schedules.

  • Keep analysis fresh between reports
  • Faster, more frequent updates
  • Capture breaking developments

Layer 2: The Investment Team (6 Agents)

Once Layer 1 has organized the data, Layer 2 agents work together like an investment committee to form a coherent view.

😊 Sentiment Analyst

Assesses overall tone across news, reports, and market signals.

"What's the mood?"

⚖️ Risk/Opportunity Analyst

Identifies top risks and opportunities with probability × impact scoring.

"What could go right/wrong?"

🔍 Data Quality Analyst

Evaluates freshness, completeness, and reliability of available data.

"Can we trust this analysis?"

🔄 Reconciliation Agent

Cross-checks qualitative claims against quantitative evidence. Exposes contradictions.

"Does the story match the numbers?"

📊 Charting Agent

Generates visual chart specifications to illustrate key thesis points.

"Show me the evidence"

🎯 Investment Orchestrator

Synthesizes all agent outputs into a final, coherent assessment. Makes the position call.

"The final decision"

How AI Outlooks Work

The Investment Orchestrator assigns one of five sentiment-based outlooks based on the combined analysis. These are not investment recommendations — they reflect our AI's assessment of the overall picture.

OutlookWhat It MeansTypical Conditions
Strong Positive
Highly favorable data signals across multiple dimensionsStrong fundamentals, reasonable valuation, positive catalysts, high conviction
Positive
Generally favorable outlook with solid supporting evidenceGood fundamentals, fair valuation, more positives than negatives
Neutral
Balanced or mixed signals — no clear directional biasMixed signals, fair valuation, stable but uncertain outlook
Negative
Concerning signals outweigh positive factorsDeteriorating fundamentals, elevated valuation risk, negative trends
Strong Negative
Significant concerns across multiple dimensionsMaterial concerns, severe data gaps, structural issues, high risk

Why sentiment labels? We use pure sentiment labels (Positive/Negative) instead of action words (Buy/Sell) to be clear that these are analytical assessments, not investment advice. Your investment decisions should consider your personal goals, risk tolerance, and circumstances.

Investor Profile Presets

Our Stock Screener includes pre-configured filter combinations that target different investment styles. Each preset combines AI analysis with relevant stock metrics to match your goals.

ProfileWhat It Filters ForBest For
Value InvestorAI Positive + Good valuation vs peers + Strong financial healthFinding undervalued quality companies
Growth SeekerAI Positive + High growth scores + Positive momentumPrioritizing revenue/earnings growth
Income FocusedDividend yield ≥3% + Strong balance sheet + No AI red flagsDividend income and stability
Quality HunterAI Strong Positive + Excellent health + Above-average performancePremium companies with high conviction
Momentum TraderAI Positive + Strong recent returns + Bullish technicalsTrend-following strategies
DefensiveLarge cap + Strong health + No AI concernsLower-risk, established companies

How it works: Each preset applies multiple filters simultaneously. For example, "Value Investor" requires BOTH a positive AI outlook AND above-average valuation metrics. This ensures you're not just relying on one signal but getting confirmation from multiple angles.

Transparency: What the AI Considers

Here are the key factors that influence our assessments:

Recent financial performance vs. expectations

Comparison to industry peers (standard taxonomy)

Market sentiment from news and events

Technical price patterns and momentum

Data quality and recency of information

Explicit contradictions between narrative and numbers

Macroeconomic factors affecting the sector

Management quality signals from reports

How it accelerates your workflow

Idea Generation

Find companies matching specific criteria instantly. "Show me profitable tech companies in Norway "

Risk Assessment

Quickly identify red flags in recent earnings reports or negative market sentiment changes.

Earnings Summaries

Get the tl;dr on a 50-page Q3 report in seconds, highlighting only what matters for valuation.

Complex Comparisons

Ask it to compare margin metrics between DNB and Storebrand over the last 3 years.

Understanding the Limitations

While our AI system is powerful, it is an analytical tool, not a financial advisor. It uses LLMs configured specifically for financial tasks, which means it can still occasionally hallucinate or misinterpret nuanced data.

Always use the AI as a starting point. Verify critical numbers before making investment decisions. SignalInvest Haughom is an independent entity and does not provide financial advice.

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