← Thursday's Architecture

Try Financial Analysis AI System 🎮

Interactive demo - See market intelligence automation in action

June 20, 2025
💹 Finance🎮 Interactive🚀 Production-Feel

From manual reports to AI-powered insights in 4 days. Now try it.

Monday: learned 3 prompts for market analysis. Tuesday: automated the full workflow. Wednesday: saw how analyst/PM/quant/ops teams use it. Thursday: reviewed the multi-agent architecture. Friday: try the actual system. Paste market data, watch AI extract metrics, generate insights, create reports for different audiences.

Try Different Scenarios

Or Select Complexity Level

💰 ROI & Cost Savings Calculator

Adjust sliders to see potential time and cost savings for your financial analysis team.

8 analysts

Number of analysts on your team

$120,000

Average annual salary per analyst

20 hrs/week

Hours per week spent on market research and report writing

85%

Expected time savings (our avg: 85-93%)

Annual Savings

$408,000

Per year with automation

Payback Period

1.5 mo

Time to recover investment

Before vs After Comparison

Annual Cost (Before)
85% reduction

Before

$480,000

After

$72,000

Time Spent (Before)
85% improvement

Before

8,320 hrs

After

1,248 hrs

Team Productivity
43% improvement

Before

100%

After

143%

Annual Savings
Infinity% improvement

Before

$0

After

$408,000

Time Saved
Infinity% improvement

Before

0 hrs

After

7,072 hrs

ROI Summary

3-Year Savings:$1,224,000
5-Year Savings:$2,040,000
ROI (Year 1):816%

These calculations are estimates based on your inputs. Actual results may vary.

🤖 Watch Multi-Agent Intelligence Collaborate

See how specialized agents work together to analyze market data autonomously

Example Scenario
Processing CloudCorp earnings miss (severe negative catalyst)
1
🎯Orchestrator
Route to Data Ingestion Agent
Detected earnings announcement, routing to ingestion
2
📥Data Ingestion
Extract metrics from text
Extracted: revenue miss 12.5%, EPS miss 27.6%, guidance cut 20%
3
🎯Orchestrator
Route to Sentiment Analysis
Negative catalyst detected, analyze sentiment
4
💭Sentiment Analyzer
Analyze CEO comments
Sentiment: -0.82 (very negative), keywords: 'frozen budgets', 'push-outs'
5
🎯Orchestrator
Route to Risk Evaluator
Severe miss + negative sentiment = high risk
6
⚠️Risk Evaluator
Assess portfolio impact
CRITICAL: Position down 18%, sector contagion risk high
7
🎯Orchestrator
Route to Insight Generator
Generate actionable insights for PM
8
💡Insight Generator
Create 3 insights
Generated: demand destruction, valuation compression, analyst capitulation
9
🎯Orchestrator
Route to Report Writer
Insights ready, create multi-format reports
10
📄Report Writer
Generate 3 reports
Created: institutional brief, retail summary, internal memo
11
🎯Orchestrator
Route to Alert System
High-risk event, send immediate alerts
12
🚨Alert System
Send urgent notifications
Alerts sent: PM (immediate action), Risk (portfolio review), Ops (monitoring)
💡
No human intervention required. Orchestrator made 7 routing decisions autonomously based on data severity, sentiment, and risk levels. Each agent specialized in one task, then passed results to next agent. This is true multi-agent collaboration - not a single AI doing everything.

🛠️ Build Your Own Finance Workflow

Pick agents from the palette below to build your custom workflow, then simulate execution.

Available Agents (12)

Your Workflow

Add agents above to build your workflow

How to Use This Demo

  1. 1Select a scenario button (Tech Bull Run, Earnings Miss, M&A Wave, etc.)
  2. 2Click 'Process Market Data' to watch AI extract metrics in real-time
  3. 3See extraction → insight generation → report creation steps animate
  4. 4Toggle between Analyst/PM/Quant/Ops views to see different perspectives
  5. 5Try all 5 scenarios to see how system handles different situations
  6. 6Check 'Watch Agents Collaborate' to see multi-agent workflow in action
🚀

Want This Built for Your Investment Team?

This demo shows what's possible. We build production-ready financial analysis systems custom to your workflows, integrated with your data sources (Bloomberg, FactSet, internal databases), and compliant with your regulatory requirements.