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Many of our subscribers take our data and feed it straight into their own AI systems. What goes into this data feed, and how can you see it. The video explains that clearly.
That was my answer when the AI question came up on a call Boardy set up for me this week, with a family office in Singapore.
It’s a fair question. You can now point a model at public filings and get a tidy, bespoke write-up for a small portfolio in minutes. A lot of that output is genuinely good, and I’m not going to pretend otherwise.
But a model writes from whatever you give it. Give it the same public information everyone else has and you get a well written version of what the market already knows.
So the scarce part is the input. At Helix we rate all 500 S&P 500 companies on eight factors. The signals are built to pick up fundamental quality that is expected to decline quarters before it shows up in the reported numbers. A news search won’t hand you that.
The other scarce part is that nobody is in the loop. Our feeds are rules-based and coded onto our server. A subscriber connects their portfolio management system and pulls the data in directly. Nobody at our end is deciding which stock makes it in today. There is no discretion to drift, and no one to second-guess on a bad week.
I’ve noticed the AI question changes the temperature in almost every room I’m in right now. Questions about method are easy to talk through. This one lands on identity, because it sounds like it’s asking what the research team is for.
My view is that the team’s job moves upstream. You decide what goes into the model, and you hold a process that doesn’t bend when the output looks convincing.
If your firm has put AI on top of its research this year, what are you actually feeding it?
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