The next wave of AI in a fund isn't another dashboard — it's agents that do the analyst's actual work: pull the real data, reason over it, and hand back a cited answer. And the people who know the questions — analysts, PMs, risk and compliance officers — should be able to build those agents themselves, with a prompt. No engineers. No six-month project.
Most "AI for finance" is a chat box bolted onto a dashboard. Agentic is a different thing entirely.
A chatbot answers questions about data you still have to find, clean, and interpret yourself. It's a faster search box — helpful, but it doesn't move the work off your plate.
An agent goes out to the sources, gathers what's relevant, reasons over it, and returns the finished thing — a cited memo, a peer comparison, a flagged risk — ready for a human to check.
The unlock isn't replacing people — it's leverage. One analyst directs a dozen agents running in parallel instead of doing a dozen manual pulls by hand.
The people who know what to ask aren't engineers — and they shouldn't have to be. Describe what you want in plain language, and the platform assembles a governed agent for you. The barrier to a new agent drops from a quarter-long project to a paragraph.
Tell it what you want, in plain English — the question, the sources, the output.
It composes an agent from governed, entitlement-checked skills — no code.
The agent gathers real data and produces a cited, checkable deliverable.
Every claim traces to its source; a person reviews and signs off.
A few examples — the point is that a desk composes its own, for its own questions.
Cited Q&A and PM-ready memos across thousands of SEC filings — with a source behind every line.
Turn scattered public data into a clean briefing on any company — business, filings, risks, and recent moves.
Monitor the SEC, CFTC, Fed, OCC and FDIC and surface only what matters to your book — nightly.
Summarize calls, extract guidance, and compare quarter over quarter across a coverage list.
Standing agents that watch for exposure, concentration, and exceptions — and raise a hand when something moves.
Sourced first drafts of investment memos and committee decks — so analysts start from 70%, not a blank page.
Everything above runs on public data. The bigger unlock is your own. Our forward-deployed engineers connect your internal, proprietary sources — positions, risk parameters, market data, and research — into the same governed layer. Once it's wired in, anyone on the desk can write agents that operate directly on that data — with the same citations, entitlements, and audit trail as everything else.
The reason most enterprise AI stalls between a great demo and production is everything that surrounds the model. That's the part this is built around.
Every answer is built from real source documents, with a citation behind each claim. No hallucinated numbers.
Agents respect who is allowed to see what. Permissions are enforced at every step, not assumed.
Every step is traceable end to end — what the agent read, what it concluded, and why. Built for the examiner.
Agents draft and gather; people decide. Judgment — and accountability — stays with your team.
This isn't a whitepaper. We've built a working platform where governed agents run live over public-data corpora — SEC EDGAR filings and regulatory feeds — producing cited answers and PM-ready memos right now. It's the fastest way to see what agentic, applied AI actually looks like on a desk. Let's do a live walkthrough over one of your use cases.