Driven

Product Introduction

1. Definition: Driven is an AI-powered investment agent platform, a specialized category of agentic AI and financial technology (FinTech) software. It functions as an integrated workspace where autonomous AI agents perform investment research, market monitoring, strategy building, and trade execution.
2. Core Value Proposition: It exists to consolidate the fragmented investment workflow into a single, AI-driven environment. Its primary value is turning market insight into actionable investment decisions, eliminating the need for investors to manually switch between dozens of disparate data sources, analysis tools, and brokerage platforms. Keywords: AI investment agent, investment workflow automation, consolidated investment research platform.

Main Features

1. 260+ Integrated Investment APIs: This feature provides programmatic access to a vast array of live financial data. How it works: The platform aggregates APIs from providers like Financial Modeling Prep (FMP) to deliver real-time quotes, fundamentals (income statements, balance sheets), ownership data, options chains, ETF holdings, macroeconomic indicators, and cryptocurrency prices for US, Hong Kong, and A-share markets. This creates a unified data layer for all agent analysis.
2. Institutional-Grade & Custom Skills (Skill Store): This is a library of pre-built and user-generated analytical modules. How it works: Skills are specialized prompts and workflows that instruct the AI agent on specific analytical methodologies, such as a Buffett-style value analysis or a Markowitz portfolio optimization. Users can create custom Skills or install shared ones from the Skill Store, allowing the AI to execute complex, repeatable analysis without manual prompting each time.
3. 24/7 Proactive Monitoring & Autonomous Execution: This feature enables automated market surveillance and action. How it works: Users can configure scheduled tasks (e.g., "scan for earnings surprises daily at 6 AM") that agents run autonomously. The agents monitor real-time data feeds against user-defined parameters (playbooks), spot signals, and can execute predefined strategies, such as rebalancing a portfolio or placing a trade, with full audit logs of every action taken.
4. Multi-Model AI Core (OpenClaw Experience): The platform is model-agnostic, integrating several frontier large language models (LLMs). How it works: It leverages models like Anthropic's Claude, Google's Gemini, and OpenAI's GPT as reasoning engines behind its agents. This "zero configuration" access allows the system to choose or allow user selection of the optimal model for different analytical tasks, such as nuanced financial report summarization or quantitative data interpretation.
5. Conversational Order Execution: This feature bridges research and action through a natural language interface. How it works: Within a chat interface, users can query real market data, discuss analysis, and directly instruct the agent to execute trades (currently paper trading) based on the conversation context. This enables a seamless flow from idea generation ("analyze NVIDIA's Q4 margins") to execution ("place a limit order for 10 shares at $950").

Problems Solved

1. Pain Point: Fragmented and inefficient investment research workflows. Investors waste significant time context-switching between brokerage platforms, financial data terminals (e.g., Bloomberg, Yahoo Finance), spreadsheet models, news aggregators, and note-taking apps, leading to missed opportunities and cognitive overload.
2. Target Audience: The primary user personas are active retail investors, solo portfolio managers, quantitative analysts, and fintech enthusiasts. It specifically targets individuals managing their own capital or small funds (evidenced by trust from managers overseeing $500M+ in assets) who lack the resources for a full human research team but demand institutional-grade tools.
3. Use Cases: Essential scenarios include: 1) Daily Market Scan: Automating the pre-market review of news, analyst upgrades/downgrades, and unusual options activity. 2) Deep-Dive Due Diligence: Conducting a comprehensive fundamental and technical analysis of a new stock idea using multiple Skills and live data APIs in one session. 3) Portfolio Rebalancing: Setting a playbook to monitor portfolio drift and automatically generate and execute rebalancing trades when thresholds are breached.

Unique Advantages

1. Differentiation: Unlike generic AI chatbots (e.g., ChatGPT for finance) that provide textual answers without reliable data or action, Driven combines verified data, specialized analytical modules (Skills), and execution capability. Compared to traditional platforms like Bloomberg Terminal, it is more accessible, AI-native, and automates the analytical labor rather than just presenting data.
2. Key Innovation: The integration of a Skill Store within an agentic AI framework for finance. This moves beyond simple prompting to a reusable, community-shared library of vetted investment methodologies. This turns the AI from a generalist assistant into a customizable team of specialist analysts (e.g., a value analyst, a quantitative strategist) that can be composed into automated workflows (playbooks).

Frequently Asked Questions (FAQ)

1. What is Driven AI and how is it different from using ChatGPT for stock research? Driven is a dedicated AI investment agent platform that integrates live, reliable market data from 260+ APIs and enables direct action, whereas ChatGPT provides general text responses based on outdated or unverified internet data with no connection to real-time markets or trading accounts.
2. Can Driven AI execute real trades automatically? As of now, Driven supports paper trading (simulated trades) through conversational order execution. The platform indicates live trading functionality is coming soon, allowing for automated or supervised trade execution based on agent signals and user-defined playbooks.
3. What kind of investment data and markets does Driven cover? The platform provides comprehensive data for US equities, Hong Kong stocks, and China A-shares. It also includes multi-asset context through data on ETFs, US options, macroeconomic indicators, cryptocurrencies, foreign exchange (FX), and commodities.
4. Who is the target user for the Driven AI investment agent? Driven is designed for active individual investors, self-directed portfolio managers, and financial analysts who seek to automate their research and monitoring workflow. It is particularly valuable for those managing significant personal capital or small institutional funds who want an "AI team" to enhance their decision-making process.
5. How does the "Skill Store" work in Driven? The Skill Store is a marketplace where users can browse, install, and share custom-built analytical modules. These Skills encode specific investment strategies or research methodologies (e.g., "Discounted Cash Flow Analysis," "Momentum Screener"), allowing users to expand their AI agent's capabilities without needing to code complex prompts from scratch.