AI agents that run the work, not the demo
Ward Consulting AI designs, deploys and manages fleets of AI agents for businesses of every size. Each agent owns one job, checks its own work before it acts, and writes down what it did. We built it first for our own company, Z-Clear. Now we build it for yours.
What we do
Every engagement starts the same way: we find the repetitive work that eats your week, give each piece to a dedicated agent, and put a scorecard on it so you can see what it did.
SMALL · 1–25 people
Typical fleet: 3–5 agents
MEDIUM · 25–250 people
Typical fleet: 8–20 agents
LARGE · 250+ people
Typical fleet: 20+ agents, per department
Case study · Z-Clear Anti-Fog, Ogden, Utah
Z-Clear makes anti-fog paste and sprays and sells through event booths, Amazon, Walmart, wholesale and its own website. Every figure below comes from Z-Clear's books and the fleet's own scorecards and run logs.
saved on hotel rooms and rental cars by one agent. Remy shops every event trip, re-checks bookings before free cancellation runs out, and flags a cheaper option when one appears. That is about $24,000 a year from a single job.
for the owner's inbox every morning, seven days a week. Iris reads it first, sorts it and flags what needs a person, so the day starts on what matters. That is about seven hours back every week.
The business the fleet runs
The website, May 1 – Sep 27, 2026 vs the same dates in 2025
September counts both years through the 27th. Hover a bar for the exact number.
| Month | 2025 | 2026 |
|---|---|---|
| May | 2,016 | 2,944 |
| Jun | 1,830 | 3,485 |
| Jul | 2,449 | 6,732 |
| Aug | 2,001 | 12,431 |
| Sep | 2,100 | 6,846 |
What the agents did
Figures as of September 27, 2026, from Z-Clear's books, Shopify, scorecards and run logs. Measured results, not projections.
The Z-Clear fleet
Each agent has a name, a charter and a scorecard. This is the actual roster running Z-Clear today, across its two fleets. Yours will be built around your jobs.
From the run logs
Real entries from Z-Clear's agents, in plain English. Agents shop, compare and recommend. Anything that spends money waits for a person to say yes.
Found a 2-bedroom rental for an 11-night fair that was cheaper than the one booked and half the drive to the booth. Re-priced it live four days later, before free cancellation ran out.Remy · lodging · Aug 2026
Checked 33 alternatives for another fair and said to stay put. The cheapest one cost more than what was already booked, for half the bedrooms.Remy · lodging · Aug 2026
Caught that a booking site's search totals leave out tax, so prices looked up to 17% cheaper than they were. Every quote since is opened and priced all-in.Remy · lodging · Aug 2026
Asked where the crew lived before pricing four rental cars. Three trips turned out to be drives from home, so only one car was needed. Then priced that one across every class.Cal · events · Sep 2026
Found Alamo cheaper than Enterprise in every car class for that trip, with free cancellation, so there was no reason to wait to book.Cal · events · Sep 2026
Spotted the owner booked at two shows 40 miles apart on the same day after a crew change, and flagged it before the weekend came.Cal · events · Sep 2026
Found a scheduled job that reported success 61 times while the ads agent inside it never ran. Nobody would have seen it from the dashboard.Vic · CEO agent · Sep 2026
Checked the live Amazon listing before submitting new bullet points for a product with 4,491 ratings, found the approved copy was already up, and held the change instead of overwriting it.Mack · Amazon · Sep 2026
How every agent works
This is the loop each agent runs on every job. It is why the fleet can be trusted with live ad budgets and customer email.
Get started
We'll map it to agents, show you what the first 30 days look like, and quote it. The assessment is free.
hello@wardconsulting.ai