Built for the Game, Not the Hype
The AI in your building shouldn't have to guess at your sport. Teamworks AI is built inside the products your staff already run, with all the context of your data and none of the exposure
The edge was never the model
Everyone will have access to the same models. The edge is what's underneath: whether your data is connected across your entire operation, and whether it's clean enough to trust before it ever reaches the model.
What's underneath is the edge
Teamworks resolves athlete identity across every system and every point of the athlete lifecycle, running your data through a quality pipeline so the model starts from a foundation no general-purpose tool can match. The more connected your operating system, the greater the edge.
Here's where it shows up
Your data, your control
Runs inside your system of record. Your data is never sold, never exposed to other organizations, and never fed to a general-purpose model. You control how it is used.
Certifications:
ISO 27001 · SOC 2 Type 2 · ISO 42001
It speaks the language of sport
Off-the-shelf AI reads your data. Ours understands it, game by game, role by role, sport by sport, because it was built inside sport, not taught about it afterward.
Built for what's next
Teamworks AI answers your questions today and is built to work alongside your staff tomorrow. You are choosing a direction, not a demo.
How it works
And the more your program runs on Teamworks, the sharper it gets.
It's embedded where you work.
No new tab, no rip and replace. Teamworks AI lives inside the products your staff use every day.
It works across your connected, trustworthy data.
Identity is resolved across every system and cleaned before it reaches the model, so it sees the whole picture instead of one more silo.
It shows its work.
Every answer links back to the source, so you can trust it, verify it, and share it.
See it in play
AI quietly at work inside the products you already run.
Find the answer without reading the whole playbook.
Ask a policy manual or playbook a plain-language question and get the answer back, with a link straight to the page it came from. Ask, answer, source.
Fill the record just by talking.
A clinician dictates an injury note by voice, AI auto-populates the required fields, and a built-in review step keeps the human in control before submission. You review, you approve.
Log a meal from a photo.
An athlete photographs the plate, AI identifies each item and estimates portions and macros for review. Snap, review, done.
See the why behind every number.
A scout pulls any metric and the film behind it appears: the play itself, with overlays on the player and routes. See the number, watch the clip.
A straight read on AI in sport
Reed's briefing cuts through the hype on what AI genuinely does today versus what's oversold. He is refreshingly blunt about what AI can't do yet, and where the real advantage is hiding.
"AI is not a strategy. It's an engine. It can save hours. It can't make the call."
How to evaluate any AI vendor
Five questions worth asking anyone who brings AI into your building, Teamworks included. Reed walks through them here. If a vendor cannot answer these clearly, including us, take pause.
1
Where does our data live, who can see it and what are you allowed to do with it?
2
How do you handle the gap between general AI and our specific domain?
3
What happens when the model is wrong and how do we know when it is?
4
How does this integrate with everything else we use?
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