Oxelis
They fail everywhere around it. A project starts with "we should do something with AI" instead of a problem someone actually owns — so there's no real budget to finish it and no pressure to use it. A demo gets built that works on five hand-picked examples, and then stalls the moment it meets real input, edge cases, and the boring 80% of robustness no one wanted to pay for. Nobody measured whether it was good enough, so nobody dares flip it to live. It stays "promising."
Oxelis is built around the parts that actually decide whether AI ships: starting from a problem worth solving, checking the value before building, handling the unglamorous plumbing, and putting it into a workflow people keep using. One engagement, end to end — no handoffs to people you'll never meet again.
And when the value math doesn't add up, we say so. A cheaper tool, a small process change, or something off-the-shelf is often the better answer — and telling you that is part of the job.