Question 1

How is AdvisorIQ different from consumer AI assistants?

Accepted Answer

Consumer AI assistants hallucinate — they generate plausible-sounding answers without verifying facts or citing sources. AdvisorIQ uses Retrieval-Augmented Generation (RAG) to ground every answer in real data: SEC filings, FRED economic data, financial news, and your uploaded client documents. Every claim includes an inline citation linking to the source document and page number. You get research you can actually trust with your fiduciary duty.

Question 2

What data sources does AdvisorIQ use?

Accepted Answer

AdvisorIQ synthesizes data from SEC EDGAR (10-K, 10-Q, 8-K filings), FRED (Federal Reserve economic data), financial news feeds, prediction markets, market intelligence, and any documents you upload (PDFs, financial plans, prospectuses). All sources are cited inline so you can verify every claim.

Question 3

Do I need technical expertise to use AdvisorIQ?

Accepted Answer

No. AdvisorIQ is designed for financial advisors, not engineers. You ask questions in natural language — the same way you'd ask a research analyst — and get structured, cited answers in seconds. Upload documents by drag-and-drop. Export audit logs as PDF or CSV with one click.

Question 4

How does the audit trail work?

Accepted Answer

Every query, every answer, and every citation is timestamped and stored in an immutable audit log. You can export complete audit trails as PDF or CSV at any time, formatted for regulatory retention requirements (SEC, FINRA). Your compliance officer will love it.

Question 5

Can I use AdvisorIQ for pre-meeting preparation?

Accepted Answer

Yes — this is one of the most popular use cases. AdvisorIQ can auto-generate pre-meeting briefs that include a holdings snapshot, relevant news and SEC filings, upcoming catalysts, and prior action items. What used to take 45 minutes of manual research is ready in seconds.

Question 6

Can AdvisorIQ understand charts and images in my documents?

Accepted Answer

Yes. AdvisorIQ uses a multimodal ingestion pipeline that goes beyond text extraction. When you upload a PDF containing charts, graphs, tables-as-images, or diagrams, each page is analyzed individually. Pages with visual content are processed through a vision AI model that extracts specific data points, axis values, trends, and table structures — so when you ask about a portfolio allocation pie chart or a performance comparison table, AdvisorIQ retrieves the actual numbers from the visual, not just the surrounding text.

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