Evony Thomas

I built Archer because I kept hearing the same story.

Over 60 conversations with home care agency owners and coordinators across the country, the same moment kept coming up: someone finds out at 6am that a caregiver isn't coming. The coordinator starts calling. The client is waiting. The scramble begins.

Nobody had a system that told them a day earlier. Not because the information wasn't there, but because nobody had built the tool to surface it. That gap is what Archer closes.

Every missed shift is a coordinator under pressure, a client without care, and revenue the agency will never recover. When that keeps happening, good coordinators burn out and agencies stop growing. I wanted to change that.

Research first. Build second.

Before Archer had a single feature, it had 60 conversations. With owners running 25-caregiver operations in Dallas. With coordinators who take calls at 5:45am. With agency directors who have been doing this for 20 years and have tried every scheduling tool on the market.

The consistent finding: the data to predict most coverage failures is already inside every agency's scheduling system. It just never gets used proactively. Archer connects to that existing data, runs 11 risk rules across every upcoming shift, and shows coordinators exactly which shifts need attention, ranked by priority, updated every 6 hours.

The pilot is 30 days because the rules-based logic fires from day one. There is no training period. Within a week an agency can see which flags are landing. Within a month there is enough data to have a real conversation about value and pricing. You measure it first. That informs what comes next.

Built at SMU, focused on DFW.

Archer came out of the SMU Launch program, which supports student entrepreneurs building real companies in Dallas-Fort Worth. The DFW home care market was the right place to start: a dense, underserved operator community with a real problem and real willingness to talk about it.

The goal is not to build another scheduling platform. There are plenty of those. The goal is to add one layer that the existing tools have never had: a system that tells you what is about to go wrong before it does.