FinSight is an AI-driven financial intelligence engine built to perform deep, multi-layered research across companies, sectors, and market themes. Unlike traditional chat-based answers, FinSight replicates the behaviour of a real financial analyst by generating a transparent research plan, executing iterative discovery loops, validating information across sources, and producing structured, high-quality research reports.
The system currently includes specialised sector agents for IT and Pharma, each capable of analysing business models, financial performance, competitive landscapes, regulatory environments, and emerging trends. As research unfolds, FinSight dynamically adapts its direction—expanding, narrowing, or branching into new sub-topics based on real-time findings from search, financial documents, APIs, and sector intelligence.
Designed with a modular, scalable architecture, FinSight can be extended to support multiple sectors and advanced research scenarios. Its objective is to operate as a full-fledged AI research analyst—rigorous, transparent, and capable of delivering actionable financial insights that support investment decisions, strategic planning, and in-depth market understanding.
What FinSight Is Designed to Do
FinSight enables an AI analyst that can:
Execute iterative, multi-step research loops that go beyond surface-level summaries.
Combine insights from web search, documents, financial APIs, filings, and news.
Perform company-level, sector-level, and comparative financial analysis.
Compute financial metrics programmatically for accuracy.
Produce well-structured, deeply analysed research reports in Markdown.
Present a transparent, modifiable research plan before execution.
How FinSight Works
1. Query Analysis & Research Planning
When a user submits any finance-related question, FinSight:
Interprets the query and identifies relevant sectors.
Defines the research scope and objectives.
Outlines data sources (web search, documents, APIs).
Maps out step-by-step research workflows.
Presents the plan for user approval before the research begins.
2. Deep Research Execution
FinSight performs multi-layer exploration through:
Broad market landscape scans
Discovery-driven deep dives
Trend and pattern identification
Cross-verification from multiple independent sources
Retrieval and analysis of annual reports, filings, and financial statements
Programmatic extraction and computation of financial metrics
Iterative refinement until a thorough, end-to-end understanding is achieved
Complex queries may trigger 15–20+ intelligent research iterations.
3. Synthesis & Report Generation
Once research is complete, FinSight:
Validates all findings
Computes financial metrics accurately
Organises insights into clear, structured, domain-specific report formats
Available report types include:
Company Analysis Report
Sector Deep Dive Report
Comparative Analysis
Investment Opportunity Evaluation
Risk & Regulatory Impact Report
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