Financial Intelligence That
Reasons, Not Just Retrieves.

Every AI tool in finance searches documents. Factor actually understands how markets are connected. A causal knowledge graph, thousands of AI agents, and multi-model research, producing insights and recommendations that get smarter every day.

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Built by engineers fromGoogle DeepMind·Google Cloud·Amazon·NVIDIAwho shipped AI research agents, inference infrastructure, and platforms serving millions.

The Retrieval Trap

The industry has embraced AI for financial research, and the tools are everywhere. But they've all converged on one paradigm: search documents, summarize text, return results. Faster retrieval is valuable, but it's not understanding.

Every Tool Searches. None Understand.

Billions have been poured into AI tools that search documents faster. But search is not understanding. They find text, summarize text, and format text. None of them model why companies are connected or how events propagate through markets.

Stateless and Forgetting

Every existing tool starts from scratch every session. No persistent memory. No record of what it recommended last week, or whether that recommendation was right. Without a learning loop, these tools are as good on day 1,000 as day 1.

Summaries, Not Verdicts

When tariffs hit TSMC, a search engine finds articles about the tariff. It can’t tell you that Apple’s iPhone revenue is exposed, that the options market is underpricing this risk, and that a specific credit spread is mispriced. That requires causal reasoning, not retrieval.

The Platform

A shared knowledge graph that compounds over time, a multi-agent research engine that produces verdicts, and a platform where humans and AI agents work together to understand markets.

Shared Causal Knowledge Graph

Companies, supply chains, events, and macro indicators, all connected with timestamps and confidence scores. The graph is shared across all customers and gets smarter with every event, like a search index for financial markets, except it reasons.

Multi-Agent Research Pipeline

Thousands of long-running agents continuously ingest historical, current, and real-time data from 100+ financial sources including SEC EDGAR, earnings transcripts, options flow, macro signals, sentiment, and more. The knowledge graph is always current, never stale.

Multi-Model Verdicts, Not Summaries

Multiple frontier models independently score each company, debate each other’s reasoning, and a blind judge produces the final verdict. The output is a specific recommendation with confidence scores and causal reasoning chains, not a text summary.

Built for Humans and Agents

Analysts get beautiful research reports and trade recommendations in minutes. AI agents get structured JSON via API. One platform, two interfaces, both powered by the same knowledge graph.

Full Spectrum Coverage

Earnings analysis, options strategies, event-driven research, sentiment tracking, supply chain impact, and macro analysis, all connected through the knowledge graph. Each capability makes the others smarter.

Gets Smarter Every Day

Every event enriches the graph. Every prediction is checked against what actually happened. Correct reasoning paths strengthen, wrong ones decay. The system improves behind the scenes, compounding an advantage no one can replicate by starting later.

From Raw Data to Real Understanding

A four-stage pipeline that transforms raw financial data into structured intelligence with specific, actionable recommendations.

Ingest

Thousands of AI agents continuously watch markets, earnings transcripts, SEC filings, supply chains, options flow, sentiment, and macro signals from 100+ sources, encoding new information into the shared knowledge graph in real time.

Connect

Raw data becomes structured understanding. Companies, people, sectors, events, and indicators are linked with timestamps and confidence scores. When new information arrives, every downstream relationship updates automatically.

Reason

Multiple frontier models independently analyze the graph, debate each other’s reasoning, and a blind judge produces the final verdict. This surfaces causal connections that no amount of document search can replicate.

Deliver

Research reports with specific recommendations, price targets, and transparent reasoning chains, delivered to analysts via a beautiful platform experience, or to AI agents via structured API. Always current, never stale.

Who Factor Is For

From hedge fund analysts to autonomous AI agents, Factor is for anyone who needs financial intelligence that understands markets, not just searches documents.

Hedge Fund Analysts

The best place to research markets

Analysts spend days manually connecting earnings, supply chains, options flow, and macro signals across siloed tools. Factor replaces that workflow with a single platform where every data point is connected through a causal knowledge graph, so one analyst can cover what used to take an entire desk.

Key Benefits

Institutional-grade research reports in minutes

Causal reasoning across supply chains and events

Specific trade recommendations with confidence scores

Transparent reasoning chains for compliance

Built for How You Work

Per-seat access for analysts. Usage-based API for AI agents and trading systems. Start with one seat and expand when the research speaks for itself.

Analyst

Full platform access for individual research analysts.

Per Seat

AI-generated research reports
Trade recommendations with causal reasoning
Earnings, supply chain, and options analysis
Causal impact summaries across holdings
On-demand report generation
Email support

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Team

Volume pricing for research desks and trading teams.

Per Desk

5+ seats

Everything in Analyst
Priority report generation
Custom research templates
Team collaboration features
Dedicated account manager
Priority support & SLA

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API

Structured intelligence for AI agents and trading systems.

Usage-Based

JSON-first structured output
Real-time knowledge graph queries
Consumption-based pricing
Custom integrations
Dedicated support
SLA guarantees

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Research That Reasons, Not Just Retrieves.

A shared knowledge graph that compounds every day. Multi-model research that produces verdicts, not summaries. The platform where humans and AI agents understand markets together.