AI engineering, sized to the team that has to run it.
Most teams do not need a transformation program. They need the three to seven tools that fit how they actually work, configured properly, plus the handful of builds worth doing after that.
AI engineering is the build side of the agency: the tools, automations, and custom workflows that take work off your team instead of adding another subscription to the pile. It starts the way the marketing lines do, with a diagnostic rather than a pitch. The AI Tools Audit maps where hours actually leak, then prescribes three to seven off-the-shelf tools sized to your headcount and budget, each with its monthly cost, setup time, and hours saved per week. What comes after is scoped only if you ask for it: single automations, internal knowledge systems, retrieval over your own documents, and agent workflows that run a repeatable process end to end. Every recommendation has to survive one question, which is whether the people who have to operate it will still be using it in three months. We would rather ship one tool that sticks than seven that get abandoned.
What runs on this line
The diagnostic comes first here too, because a build quoted against a workflow nobody has measured is a guess with an invoice attached.
Find out where the hours actually go
One 45-minute discovery call, a seven-section report, and a four-day quick-start plan sized to your headcount and budget. Five business days, $999, credited toward whatever you build next with us.
Questions about AI engineering
What does AI engineering mean here?
Practical build work, not research. Choosing and configuring off-the-shelf tools, wiring automations between the systems you already pay for, standing up an internal knowledge system your team can actually ask questions of, and building agent workflows for repeatable processes. If an existing tool solves it, we say so rather than quoting a build.
Do we have to start with the audit?
For anything beyond a single well-defined automation, yes, and for the same reason as on the marketing side: we will not scope a build against a workflow nobody has measured. The audit is $999, credited toward whatever you do next with us, and the credit is portable across both audits if the review call points you at the other one.
We already pay for AI tools we barely use. Is that a problem?
It is the usual starting point, and consolidation is as common an outcome as addition. Most teams have three tools doing one job badly, or a seat count that stopped matching the org a year ago. The audit maps what you already have against where the hours actually leak before it recommends anything new.
Will you build something custom?
When off-the-shelf genuinely does not fit, yes: automations, retrieval over your own documents, and agent workflows. The test we apply first is whether the team that has to operate it will still be using it in three months. Custom work that only its author can run is a liability we hand you, so we scope for the operator, not the demo.
How does this line relate to the marketing side?
Same delivery loop, different surface. Both start with a fixed-scope audit, both are gated on honest fit, and both report against something measured up front rather than a feeling. Plenty of clients arrive for one and discover the real bottleneck is the other, so we route you accordingly and the $999 credit follows you.