Systems thinking across marketing, sales, and customer support — plus the creative engine that feeds them. We map how work actually flows, design AI-powered workflows, and connect the tools, so leads, tickets, briefs, and content stop falling between teams.
An AI workflow is a repeatable process in which AI handles defined steps — reading, tagging, drafting, routing — inside rules designed by a person, with clear handoffs to your team. It is not a chatbot bolted onto a website: it is your existing process, redesigned so the repetitive load runs itself. We build them with systems thinking because most growth problems do not live inside one team — they live in the handoffs between marketing, sales, and support.
New lead → enrichment → scoring → routed to the CRM with a Slack alert and a first-touch draft ready for review.
Inbox and WhatsApp triage: category and urgency tagging, suggested macros, escalation rules, weekly quality digest.
Brief → AI draft → human review → approval → calendar — plus a repurposing engine that turns one pillar piece into a week of posts.
Pre-built flows we adapt to your stack — typically live in days, not months. Everything above is possible; these are the three we deploy most.
We analyze how work actually flows between marketing, sales, and support — and where it leaks
We design the workflows and playbooks around the leverage points we found
We pilot the redesigned workflow with one team or segment first
We prove it with cycle time, response time, and conversion through the funnel
We roll it out across teams — documented in playbooks people actually use
Every engagement runs on one loop — Analyze → Create → Test → Prove → Scale — and every cycle feeds the next: better ads, faster flows, a sharper system.
Our team has run an 80+ person support operation — writing the playbooks, cutting ticket resolution time 70%, and lifting efficiency 20% — and built the creative-ops systems (libraries, testing roadmaps, production calendars) used across 10+ brands. We design workflows the way operators do: from the inside.
Yes — until maintenance eats you. ChatGPT, n8n and no-code tools build the pieces; what they don’t give you is a system: hypothesis-driven priorities, someone reading results, and upkeep when APIs and policies change. Loose automations break silently; an orchestrated system compounds. Read the full comparison: DIY with AI vs. a growth studio →
We design the system and implement it with proven AI and automation tools — tool-agnostic, built around your stack. When a project calls for deep custom engineering, we bring specialist partners in; the system design and the accountability stay with us.
A working session on the metrics, refinements to the flows, updated playbooks, and a short report: what improved, what we’re changing next.
With a process audit: one to two weeks mapping how work actually moves between marketing, sales, and support. You get the map, the leaks, and a prioritized redesign plan — useful even if we stop there.