See examples of the work
Review example engagements across support, service operations, and analytics to see how BaobabCat approaches execution.
~/baobabcat/home
home
deploy ai. stay human.
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Strategy if needed. Implementation when useful. Training when adoption matters.
~/value-proposition
what we do
AI work that lands in operations
BaobabCat works with teams that want less AI theater and more functioning systems. We map where AI belongs, build the workflow, train the humans around it, and leave the business with something that can keep running.
$ cat operating-principles.txt
Focus on operator pain, not abstract AI ambition. Keep the human handoff visible. Ship the smallest useful system first. Train the team that has to trust it.
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how engagements run
- Find the workflow that should change first.
- Define business outcomes before tooling.
- Build the smallest useful system.
- Train the team that has to live with it.
- Iterate from actual usage, not promises.
~/services
view services
Services built for operational work
BaobabCat helps teams choose the right AI work, build it into the real workflow, and support the people who have to use it every day.
$ ls services/
Strategy, automation, custom systems, training, analytics, and OpenClaw for teams that need practical deployment support.
AI Strategy & Readiness
Prioritize use cases, identify constraints, and set a roadmap the team can execute.
AI Workflow Automation
Reduce repetitive work across support, intake, handoffs, and internal operations.
OpenClaw Deployment
Deploy OpenClaw as one service option when a multi-channel assistant actually fits the business.
Custom AI Solutions
Design internal copilots, document systems, and bespoke workflow tools around real constraints.
AI Training & Enablement
Help leaders and teams adopt tools with policy, process, and confidence.
AI Data & Analytics
Turn operational data into forecasts, reporting, and decision support your team can trust.
~/blog/recent
read all posts
Recent blog posts
Practical writing on AI operations, implementation, deployment choices, and where tools like OpenClaw actually fit.
Why AI pilots stall after the demo
What actually kills an AI pilot after leadership approval, and what a disciplined rollout looks like instead.
The age of AI agents: what is actually working
A longer read on where agents produce leverage and where teams are still kidding themselves.
How we cut support response time by 80%
A breakdown of queue design, triage logic, and escalation rules that made the number believable.
Need help turning AI into working systems?
Reach out with the workflow, queue, or handoff that needs attention. If you already know the problem, say it directly. If not, describe where the team is getting stuck.