Services / AI integration & automation
We help marketing teams identify where AI or automation can genuinely help, connect it to the right data and tools, and ship systems with human review, clear ownership, and measurable outcomes.
Where we fit
Most AI projects begin with a tool and go looking for a problem. The result is usually an impressive demonstration that nobody trusts enough to use. We begin with the work itself: where time is lost, where judgment matters, what data is available, and what a useful outcome would look like.
Then we choose the simplest dependable approach. Some steps need conventional automation. Some benefit from an AI model. Some should remain human. The goal is not to put AI everywhere. It is to make the work meaningfully better.
What we help build
Discover
We map how work moves through your team, identify the delays and repetitive steps, and rank potential improvements by value, feasibility, risk, and cost. You leave with a practical roadmap, including the places where AI is not the answer.
2 to 3 weeks · fixed fee
Find
Permission-aware assistants grounded in the documents, policies, product information, and research your team already maintains. Answers include sources so people can verify them instead of trusting a confident guess.
Prototype, evaluate, then expand
Improve
Systems that help with research, briefs, content adaptation, quality checks, and campaign handoffs while keeping subject-matter judgment and approval with your team.
Focused workflow project
Connect
Connect AI and automation to your CMS, CRM, analytics, project tools, and approved data sources. We design the handoffs, permissions, fallbacks, and human review steps that turn a model into a dependable workflow.
Scoped integration project
Non-negotiables
A working prototype is only the beginning. A production system needs clear boundaries, evidence that it works, and a team that understands what happens when it does not.
Consequential work has a named human reviewer. Automation supports judgment rather than quietly replacing accountability.
The system sees only the information it needs. Existing access rules carry through wherever the underlying tools allow it.
We define useful, acceptable, and failed outputs before launch, then test the system with representative work from your team.
Your team receives the architecture, operating guidance, known limitations, costs, and an exit path that does not depend on us.
Honest tool selection
Rules-based software is cheaper, faster, and more predictable when the rules are already known. We will not add a model where a form, integration, or small script would solve the problem better.
When AI is warranted, we make its limits visible. Your team knows what information it can access, how its output is checked, what it costs to run, and when a person needs to take over.
Next step
We will map the work with you, identify where automation or AI could help, and tell you honestly when a simpler solution would be better.