Financial Research
Investment Intelligence Platform
AI-Powered Investment Research
A full-stack investment research platform that ingests diverse financial content sources, runs LLM-powered synthesis with vector search, and delivers comparative analysis, smart dashboards, and multi-agent investor panel debates for institutional-grade decision support.
Financial Research
AI-Powered Investment Research
The Story Behind the Build
From problem to lasting impact — how we approached Investment Intelligence Platform end to end.
The Challenge
Investment teams were drowning in unstructured data scattered across SEC filings, earnings transcripts, newsletters, and social media. Manual research took days, insights were lost, and there was no way to query years of accumulated knowledge in real-time. The team needed an AI-native platform that could ingest, synthesize, and make searchable thousands of financial documents.
Our Solution
We built a multi-source ingestion pipeline that processes PDFs, web pages, podcasts, and social posts into structured embeddings. A smart query router classifies each question and routes it to the optimal retrieval path. A virtual investor panel of AI-simulated personas debates investment theses in real-time, giving analysts multiple perspectives instantly.
The Impact
The platform transformed a days-long research process into seconds. Analysts can now query a knowledge base of thousands of financial documents, get instant comparative analysis, and watch AI agents debate investment theses from multiple perspectives.
Key Results
Concrete outcomes that made the difference for Investment Intelligence Platform.
8 configurable LLM purposes across the platform
Multi-source ingestion from 5+ content types
Real-time streaming responses for analyst queries
Institutional-grade investment debate simulation
Project Details
Timeline
12 months
Team Size
5-person team
Technologies
8 core tools
What We Built
Multi-source ingestion: SEC filings, earnings calls, newsletters, podcasts, social media
RAG-powered synthesis with three-tier chunking and 3072-dimension embeddings
Smart query router with multi-class routing (structured, RAG, hybrid, direct)
Virtual investor panel with 4 AI personas and multi-agent Socratic debate
Macro dashboards with live commodity pricing and statistical anomaly detection
Framework extraction from investment books and PDFs
Project Timeline
From initial discovery to successful launch — our proven delivery process.
1
Discovery
Architecture & Data Modeling
Designed the ingestion pipeline, vector storage schema, and LLM purpose configuration system.
2
Design
Query Router & Synthesis
Built the smart query router with multi-class classification and three-tier chunking for RAG.
3
Development
Platform & Dashboards
Implemented macro dashboards, virtual investor panel, and multi-agent debate with streaming.
4
Launch
Framework Extraction
Added investment framework extraction from books and PDFs, plus statistical anomaly detection.
Measurable Impact
5+
Content Sources
3072
Embedding Dimensions
8
LLM Purposes
47
DB Migrations
Before & After
A clear picture of how Investment Intelligence Platform improved after our collaboration.
Research Time
99% fasterBefore
2-3 days
After
< 30 seconds
Document Coverage
100% coverageBefore
Manual sampling
After
Full corpus search
Analysis Perspectives
4x viewpointsBefore
Single analyst
After
4 AI panelists
Data Sources
5x breadthBefore
1-2 sources
After
5+ integrated
Outcomes
Key Results Delivered
8 configurable LLM purposes across the platform
Multi-source ingestion from 5+ content types
Real-time streaming responses for analyst queries
Institutional-grade investment debate simulation
Built With
Next.jsFastAPIPostgreSQLpgvectorLangChainGoogle GenAITerraformDocker
Mining Analytics Platform
BTC Mining Operations Dashboard
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