Finance Agent
Real-time market insights and deep-dive company analysis for smarter investing.
Trusted by
Built on proven enterprise-grade generative AI technologies used by leading financial institutions, with robust provenance and audit-trail capabilities.
Success Story
JPMorgan Chase used generative-AI tools and achieved a 20 % increase in gross sales for its asset & wealth-management business between 2023 and 2024
Integrates with
Problem
Finance teams and investors often spend excessive time locating, aggregating and interpreting company filings, earnings-calls, market commentary and sector data. Valuable human time is consumed by data gathering rather than strategic insight. Additionally, the pace of market change means manual workflows struggle to keep up with real-time shifts and emerging risks.
Solution
The Finance Agent automates the tedious parts of research: retrieving the latest disclosures, summarising earnings-call commentary, comparing peer metrics, flagging anomalies and generating clearly structured reports. It lets you ask a natural-language question and receive a polished output within minutes, freeing you to focus on strategy, communication and decision making.
Result
Users can expect significantly faster turnaround on company deep-dives, higher insight quality and the ability to respond in near-real time to market events—leading to better client outcomes, sharper internal decision making and more productive teams.
Use Cases
The Finance Agent is your on-demand AI analyst that empowers finance professionals, investors and corporate teams with high-quality company analysis, sector breakdowns and investment-strategy insights. You can ask it: “What’s the competitive positioning of Company X?”, “How has their margin evolved over the last five years?”, “What does recent earnings commentary imply for stock Y?”, or “Which sectors are poised for growth in the coming 12-24 months?” Rather than simply regurgitating data, the agent synthesises multiple sources (historical financials, filings, earnings-call transcripts, analyst commentary) and delivers structured outputs: executive summaries, SWOT-style assessments, valuation comparables and scenario-driven forecasts. It enables you to spend less time digging through raw data and more time forming strategy, making decisions and communicating with stakeholders. The agent is built with enterprise-grade reliability and can be customised to your workflow: integrate your own company universe, restrict coverage to specific sectors, and maintain provenance and audit trails of insights. Whether you are an equity analyst, a wealth-management adviser, a CFO, or an investment team member, this agent gives you a strategic edge.
Integrations
Connect to your existing tools seamlessly
Technology Stack
Automation
Automation
Infrastructure
Implementation Timeline
Kick-off & Requirements Gathering
1 weekConduct discovery sessions to define objectives, data sources, integration needs, and user expectations. Establish project scope, KPIs, and timeline.
Data-Source Connections & Ingestion Setup
1–2 weeksConnect to financial data APIs (e.g., SEC/EDGAR, Bloomberg) and internal databases. Configure pipelines for automated ingestion and normalization of structured and unstructured financial data.
Agent Prompt-Engineering & Fine-Tuning / Account Mapping
1–2 weeksCustom- train and optimize the AI’s responses for financial analysis use cases. Map roles and access levels, align tone and terminology to client workflows, and validate output quality.
User-Interface Setup & Export Workflows
1 weekBuild the interface for user interaction (dashboard or chat interface). Configure export options to Excel, PowerPoint, or PDF for seamless reporting.
Testing, Training & Roll-Out
1–2 weeksConduct end-to-end testing, user acceptance validation, and model accuracy checks. Deliver user training sessions and finalize production deployment.
Support Included
Comprehensive documentation with step-by-step workflow setup, API configuration guides, integration instructions. Optional onboarding call and email support during the launch phase.
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