> ## Documentation Index
> Fetch the complete documentation index at: https://help.podiummarkets.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Chat with Ivy — AI-Powered Research for Active Traders

> Use Ivy's conversational interface to research stocks, analyze market conditions, get portfolio insights, and run AI-powered research agents.

Ivy is Podium Markets' AI trading assistant — a conversational interface built directly into the platform so you can research stocks, interpret market conditions, and surface actionable context without leaving your workflow. Ask questions in plain English and Ivy responds with data-backed analysis drawn from live market feeds, filings, news, and more.

## Starting a conversation with Ivy

To open the chat panel, click the **Ivy** icon in the upper right hand corner of the dashboard. You can also type directly in the chat panel, and press send to enter the primary Ivy chat interface.

Ivy is designed to handle a broad range of trading-related questions across multiple dimensions of the market:

<CardGroup cols={2}>
  <Card title="Earnings & Fundamentals" icon="chart-line" href="/ivy/chat-and-research">
    Ask about upcoming earnings dates, analyst estimates, historical beat/miss rates, and key risks heading into a report.
  </Card>

  <Card title="Sector & Macro Outlook" icon="globe" href="/ivy/chat-and-research">
    Get a read on sector rotation, macro headwinds, or how a Fed decision might ripple through specific industries.
  </Card>

  <Card title="What's Moving Today" icon="bolt" href="/ivy/chat-and-research">
    Ask Ivy to surface the top movers, unusual volume, or breaking catalysts across the market right now.
  </Card>

  <Card title="Portfolio Questions" icon="briefcase" href="/ivy/chat-and-research">
    Explore concentration risk, correlated positions, or how a new trade might fit within your existing holdings.
  </Card>
</CardGroup>

### Example prompts to get started

Try asking Ivy questions like:

* *"What are the key risks for TSLA going into earnings?"*
* *"Which sectors are showing relative strength this week?"*
* *"What's moving in biotech today and why?"*
* *"How correlated are my current positions?"*
* *"Give me a bull and bear case for NVDA at current levels."*

You can ask follow-up questions naturally — Ivy maintains context within a session so you can drill progressively deeper into any topic.

## Research agents

Beyond single-turn Q\&A, Ivy can launch **research agents** — autonomous multi-step workflows that gather, synthesize, and summarize information across several sources before returning a consolidated answer. Where a standard chat response might draw on a single data source, a research agent might simultaneously pull SEC filings, recent news headlines, earnings call transcripts, and analyst commentary, then stitch them into a coherent narrative.

### When to use a research agent

Research agents are most useful when your question requires breadth — for example:

* *"Give me a full pre-earnings briefing on AMZN: recent guidance, analyst sentiment, and top risks."*
* *"Summarize the last three 10-Q filings for META and flag any changes in forward-looking language."*
* *"Scan the news for anything that could move energy stocks this week."*

### How to trigger a research agent

When Ivy detects that your question warrants a multi-source deep dive, it will automatically launch an agent and show a progress indicator while it works. You can also explicitly invoke an agent by opening the agents module, activating an agent, and prefixing your prompt:

* *"Run a research deep-dive on MSFT ahead of next week's earnings."*
* *"Agent: summarize recent FDA decisions that could impact MRNA."*

Ivy surfaces a structured response when the agent finishes, with clearly labeled sections and source citations so you can trace every claim back to its origin.

## Understanding Ivy's responses

Ivy structures its responses to be scannable and actionable. Long-form analysis is broken into labeled sections; lists of catalysts or risks are bulleted for quick review; data points (price targets, earnings estimates, IV percentiles) are called out inline.

A few important things to keep in mind as you work with Ivy:

* **Ivy is AI-generated.** Responses synthesize available data, but they can contain errors, omissions, or outdated information. Always cross-reference critical data points with primary sources.
* **Context matters.** The more specific your question, the more precise Ivy's response. Vague prompts produce general answers; specific prompts with a ticker, timeframe, and angle produce targeted analysis.
* **Session memory is scoped.** Ivy remembers the thread of your current session. Starting a new chat clears the prior context.

<Warning>
  Ivy's responses are for informational purposes only and do not constitute financial advice. Always conduct your own due diligence and consult a qualified financial advisor before making any investment decisions.
</Warning>

<Tip>
  Don't stop at the first response — ask follow-up questions to go deeper. If Ivy surfaces a risk factor, ask *"Can you expand on that?"* or *"How has this impacted the stock historically?"* Iterative questioning consistently produces richer, more useful output than a single broad prompt.
</Tip>
