Grupo Marista Agents Cut Hospital Claims Analysis From 72 Hours to 4 Hours
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
A random mix from the whole library. Shuffle for a new set.
Grupo Marista uses AI Enterprise agents to analyze hospital claims. Analysis that took 72 hours now takes 4 hours.
Agent ported a moderately complex workout app from web to native iOS in a couple of evenings, with a test battery.
After UnitedHealthcare denied coverage for his out-of-network spinal surgeon, Donald Grant used Claimable's AI appeal service to build an 11-page legal and medical appeal, which he emailed to the insurer's CEO, officials and reporters. UnitedHealthcare approved both the surgeon and the procedure at the in-network rate ahead of his October 14 surgery.
He just subscribed to the AI and is setting up a Strava link. The AI gives him a weekly training plan based on his goals, his past workouts, his time, and his injuries, and it got to know him fast.
A No Code MBA reviewer asked the AI to turn a six-month marathon goal into a 24-week training plan PDF. A long-horizon fitness goal converted into a structured, printable plan.
The AI is his gym trainer: he reports his sets and reps as he does them, and later that day Astra logs them into an Excel tracker, then uses the updated tracker to refresh an HTML app it built that shows his progress over time and his missed workouts.
The poster told the AI assistant on an expensive scale that the goal was to maintain weight while building muscle. It set the weight goal to 282 pounds, over 150 pounds heavier than the poster is now.
NYT reporter Eli Tan, reviewing the AI over two weeks with connected bank accounts and email, had it call his dental insurer Anthem. The AI supplied his member ID, answered the security question, waited on hold, then rang him through to the live representative.
While training on his Wattbike, he wondered if the AI Fable could crack the workout file format. It reverse engineered the format in under 10 minutes, and half an hour later there was a Python and JavaScript library plus a static viewer app.
When every Oura MCP server turned out unmaintained, the AI suggested a simpler design - a SQLite database with a cron sync - and built it. Now he's experimenting with injecting his sleep score into his agents' startup, so they give simpler, less demanding responses on days he's not all there, down to gentler perfume samples.
Every idea is a real post from someone who tried it, summarized in our words, with a link to the original. App names are swapped for plain words.