“AI automation” can sound abstract until you see what building one actually involves. Here’s the process we follow on every project, from first conversation to something running in production.
1. Feasibility & discovery
We audit the workflow in detail — every step, every handoff, every tool involved — and identify exactly where manual effort can be replaced, and what the realistic time savings look like.
2. Design the automation
We map out the data sources, the tools it needs to connect to, and the exact logic it needs to follow — built around the systems you already use, so your team doesn’t have to change how they work to benefit from it.
3. Build & test
We build it as a fixed-scope project and test it against real data before it ever touches anything live, so there are no surprises when it goes into production.
4. Launch & support
We deploy it, walk your team through how it works, and stay on for ongoing support as your processes evolve — automations should adapt as your business changes, not become one more legacy system to maintain.
Most projects go from first call to a working automation in days or weeks, not months, because the feasibility study up front means we already know exactly what we’re building. See more of what we build, or book a discovery call to start with your own workflow.