FinChat (Fiscal AI) vs Consensus
FinChat vs Consensus for financial research: compare financial data Q&A (100,000+ companies) vs academic paper search (220M+ papers) for fundamental analysis, thesis validation, and evidence-based investing.
Quick Answer
FinChat and Consensus both answer research questions with citations but draw from completely different sources. FinChat searches financial statements, filings, and earnings transcripts for 100,000+ public companies — ideal for fundamental company analysis. Consensus searches 220M+ peer-reviewed academic papers — ideal for evidence-based research on financial theory, economic relationships, and investment strategies. Use FinChat to research a specific company. Use Consensus to find what academic research says about a market phenomenon or investment thesis.
FinChat (Fiscal AI)
FinChat is an AI-powered financial data Q&A engine covering 100,000+ public companies globally. Ask natural language questions against any company's financial statements, filings, and earnings transcripts instantly.
Pricing
$0/mo(Plus: $35/mo, Institutional: $0/mo)
Agent Type
Assistant
Key Use Cases
- ✓Company data Q&A — natural language questions against financial statements, filings, and earnings transcripts for any public company
- ✓KPI and metric lookup — instantly surface specific financial metrics, growth rates, and operating KPIs from company filings
- ✓Earnings transcript analysis — query specific statements, themes, and guidance from earnings calls using natural language
- ✓Peer comparison — compare financial metrics across competitor sets with natural language queries
- ✓Financial model data export — pull structured financial data into spreadsheet-compatible format
- ✓Segment and geographic revenue analysis — decompose revenue by business segment and geography
Deployment
Cloud
AI Model
FinChat AI — LLM-based financial data Q&A engine trained on structured and unstructured financial data. Also available as a connector in Perplexity Finance mode.
Platforms
Web
Learn more →Consensus
AI-powered academic search engine that indexes over 200 million research papers. Extracts and synthesizes cited findings from peer-reviewed studies — purpose-built for evidence-based financial research, not general web search.
Pricing
$0(Premium: $9.99/mo, Teams: $8.99/mo, Enterprise: $0)
Agent Type
Assistant
Key Use Cases
- ✓Investment thesis validation — search peer-reviewed studies to support or challenge valuation assumptions and investment hypotheses with cited evidence
- ✓Risk factor research — find academic research on specific risk factors, correlations, and market anomalies with confidence indicators
- ✓Due diligence support — research company fundamentals, industry dynamics, and competitive moats from academic literature
- ✓Asset pricing and valuation — access research on discount rates, beta estimation, DCF methodology, and alternative valuation approaches
- ✓Regulatory and policy research — find peer-reviewed analysis of regulatory changes, policy impacts, and compliance best practices
- ✓ESG and sustainability analysis — research ESG metrics, carbon pricing, sustainability disclosures, and their financial impacts from academic sources
Deployment
Cloud
AI Model
GPT-4 for summaries and Copilot analysis; proprietary consensus engine for evidence synthesis across multiple papers
Platforms
Web, iOS, Android
Learn more →Real-World Scenarios
You want to research a specific company's financials, earnings history, and KPI trends
You need detailed financial data on a specific public company — revenue trends, margin analysis, segment breakdowns, and key performance indicators from filings and earnings transcripts.
You want to validate an investment thesis or financial theory against peer-reviewed academic literature
You have a hypothesis about a market relationship, risk factor, or investment strategy and want to see what peer-reviewed academic research says — with cited evidence and confidence signals.
You want a free tool for occasional research
You need access to financial research tools but only occasionally. You want to avoid subscription costs while still getting value from AI-powered research.