AI for financial services
Advisory and investment firms spend their week on everything around the advice — client education, meeting prep, reporting. We automate that work, so your people spend their time with clients.
In financial services the constraint isn't expertise — it's the hours of repetitive, client-facing prep that surround every piece of real advice. Explaining the same concepts to each client, prepping for review meetings, and producing the same reports on a recurring cadence all scale linearly with headcount.
That's the layer AI handles well — the education and the operations around the advice, never the advice itself. A licensed professional stays responsible for every recommendation; the agent just removes the busywork. Here's a portfolio-aware education product we built.
What financial firms keeps asking AI to do
Client education at scale
Turn the concepts you explain a hundred times a year into personalized, on-demand education — so every client gets the depth, without booking your calendar.
Portfolio-aware content
Generate material tailored to each client’s actual holdings and goals — relevant, specific, and produced automatically rather than hand-assembled.
Meeting prep & recurring reporting
Draft review-meeting briefs and the reports you produce on a schedule, pulled from your systems — the work that quietly eats a day every week.
What we've built for financial services
Today's episode · 15 min
This Week in Your Portfolio
Lane
The analyst
Radford
The big picture
Built around your holdings
Investment education — not financial advice
Portfolio-aware client education
Project Radford — personalized investment education
Project Radford delivers a personalized investment-education podcast built around each listener’s actual portfolio — two AI hosts (a data-driven analyst and a big-picture thinker) discussing the holdings and concepts that matter to that person, in a natural 15-minute episode. It’s the clearest example of what AI does well in finance: scale the education, keep the advice with a human.
Read the Project Radford case studyWhy a custom build (and where AI stops)
Generic AI tools don't know your clients, your holdings, or your compliance posture — so they produce generic output you can't safely use. A custom build is scoped to your data and your guardrails: it personalizes to the real portfolio, stays inside the lines you set, and keeps a human at every decision point.
We're deliberate about the boundary. These systems handle education and automation — they do not give investment advice, make recommendations, or forecast returns. That line is a feature, not a limitation.
How we work
- Fixed scope and a fixed price — quoted in 24 hours, no hourly surprises.
- A working system in 4-6 weeks, with weekly demos you actually see.
- You own the code and the cloud from day one — no lock-in.
Frequently Asked Questions
Want an AI system for your financial firm for your business?
Here's how to figure out if it's the right move — without talking to a salesperson.
Spec it in Mission Control
Answer a few questions and our AI drafts a build spec for your idea — free, no signup.
Pressure-test it anywhere
Paste the spec into Claude, ChatGPT, or any AI for a free second opinion on feasibility and cost.
Talk to us if it's a fit
When you're ready, we'll scope, price, and ship — same studio that built this.