AI Teammates That Run the Back Office

The Problem

Woodward Solutions runs several small businesses at once — TourneyHunter, Compete.News, RFP Harvest, and client work. Each one needs the same unglamorous upkeep: checking that the data is right, keeping an eye on competitors, answering organizer emails, and posting something worth reading on social media. None of it is hard. All of it takes time, and it's the first thing to slip when the week gets busy.

Hiring an assistant for each business didn't make sense. Chatbots didn't help either — they wait for you to ask a question. We needed something that does the work on its own and checks in when a decision is needed.

The Solution

We built a team of AI agents on Grok Bot, xAI's agent platform. Each agent has its own cloud computer with a browser, files, and a terminal, so it can do the same multi-step work a person would: log into tools, read pages, pull numbers, draft the email, and file the result. It runs around the clock, and it learns a routine by being shown it once.

The lead agent acts as chief of staff. Every morning it sends a short brief: what changed overnight, what broke, what competitors did, and what needs a decision today. Behind it, other agents handle research and data, and they hand work to each other in shared threads.

What It Handles Day to Day

• Daily briefs. One email each morning covering every business, ranked by what needs attention.
• Competitive intel. Watches competitors and the market, and flags launches, pricing changes, and new entrants.
• Data QA. Spot-checks live listings and sends back what it found wrong, so problems get fixed before a customer notices.
• Organizer email. Drafts outreach and replies to tournament organizers, grounded in what's actually listed for them.
• Social posting. Turns real numbers from TourneyHunter's public data feed into posts for X and other channels.

The Go-to-Market Side

Most small companies know they should post regularly and follow up with every lead. Few actually do, because it's a daily habit nobody has time for. This is where the agents earn their keep.

We gave them a source of truth to work from: a public stats feed on TourneyHunter that reports how many tournaments are listed, where, at what level, and what they cost. The agents write from those numbers, not from guesses. A post saying "January has more youth hockey tournaments than any other month" is true because the data says so, and the agent checked before it wrote it.

Email works the same way. When an organizer writes in, the agent looks up their listings first, then drafts a reply that refers to their actual events. Anything that commits money, changes a customer's data, or goes to a new audience waits for a human to approve it.

How We Thought About It

The risk with AI agents is that they sound confident while being wrong. So we kept the same rule we use everywhere: the agent can draft, research, and recommend on its own, but it has to show its sources, and it stops at checkpoints. Publishing, sending to a customer, and changing data all need a yes.

We also kept the agents out of the core systems. They read from public feeds and send their findings by email. The scrapers, database, and website run on their own code. If an agent has a bad day, the businesses keep running.

The Result

• One morning brief covering Woodward Solutions and its companies
• Competitive intel, data QA, organizer email, and social posting handled by agents
• Every post and reply grounded in real data, not guesses
• A human approves anything that goes out the door or touches customer data
• The same setup can be built for a local business in a few sessions