What I like best about AirOps is its ability to turn complex SEO and content workflows into a single, scalable system. The iterator-based workflows make it easy to scrape data, analyse SERPs, extract insights, and generate high-quality content automatically. Everything runs end-to-end in minutes, not hours, while still allowing granular control through logic and conditions. It replaces multiple tools with one flexible platform and delivers faster execution, better consistency, and measurable impact on search performance and LLM visibility.

Product is solid and helps to optimize content generation

We're piloting AirOps, so this is early hands-on, not a year in production. AI and intelligence. This is the best part of the platform, and the reason we're in. The intelligence is the real thing, especially for SEO and content work. It scouts, it handles backlinking, and it holds context across a task better than we expected. Wire in your MCP connections and it gets sharper fast, because now it's pulling from your actual sources instead of guessing. If output quality is what you care about, this is where AirOps wins. Integrations. The easy part. AirOps drops cleanly into an MCP setup, so connecting our tools and sources was quick, and those connections are what make the AI as good as it is. If you're already working in MCP, this will feel native. Support and onboarding. A real strength. Onboarding was thorough enough to get us working without a lot of trial and error, and support has been quick when we needed it. For a platform with this much going on, that counts for more than it sounds. UI and UX. Where there's the most room to improve. You get workflows, power agents, and playbooks, and all of it is capable, but figuring out how they fit together and when to reach for which takes a while. The power is all there. The work is the learning curve to reach it. Plan on leaning on that onboarding to get over the hump. Performance. The other soft spot. We've hit lag and a few bugs in normal use. Nothing that's stopped us cold, but enough to break flow and get noticed. For a tool you'd run every day, this is what we'd most want tightened. Pricing and ROI. Still TBD. We're in the pilot, so putting a number on the value right now wouldn't be honest. We'll know more once we've run it long enough to weigh output against cost. The signal looks good. The proof isn't in yet for us specifically. Where it nets out. AirOps lives and dies on its AI, and the AI is excellent, especially once MCP is feeding it context. Support has your back while you learn it. The catch is a UX that takes real work to figure out and performance that can stutter. If you want AI quality and you'll put in the ramp, it's worth a serious look. We'll report back on ROI once the pilot has legs.