Ask cross‑filing questions once. Get a complete answer.
Upload prospectuses, investor letters, and regulatory guidance. AIAM Graph RAG connects them into a single research surface with table‑aware RAG.
- “How did management’s outlook on credit quality change over the last four quarters?”
- “Compare fee structures across these three share classes and highlight differences.”
- “Summarize key risk factors mentioned for energy exposure across recent filings.”
Research speed without sacrificing diligence.
Answer broad questions that cross multiple filings, fund documents, and regulatory texts – with citations for every claim.
Cross‑issuer analysis
Ask the system to compare terms, covenants, or disclosures across multiple issuers and vintages at once.
- Side‑by‑side clause and table summaries.
- Focus on narrative, not manual paging.
What changed since last launch?
Track how fee schedules, risk language, and feature tables evolved between product iterations.
- Page‑aware search across historical term sheets.
- Flag non‑standard language with sources.
Policy & guidance navigator
Turn regulations, internal policies, and procedures into a searchable knowledge layer with explanations.
- Ask “How do we interpret X for Y product?”
- See every answer’s supporting passages.
Who this is built for
- Equity and credit analysts who live in filings, decks, and transcripts.
- Portfolio managers reviewing complex strategies across multiple products.
- Risk officers and compliance leads mapping policy to live products.
- Distribution and client teams preparing nuanced, well‑sourced responses.
Financial research is where tables matter most. AIAM’s document pipeline preserves table structure in Neo4j and builds table‑specific embeddings. Our chat system can then retrieve not just text paragraphs, but specific rows and cells that answer your question.
The agent can plan additional, targeted searches when an answer is broad – for example, exploring more filings until coverage of a topic reaches your configured threshold. That means fewer missed edge cases and more repeatable workflows.
Try table‑aware multi‑turn chat