We start with a business audit — not a tool pitch. Then we automate the workflows worth buying back, and stay on to make sure it holds past launch.
30 minutes with a founder. No BDRs, no slides.
Whether you need to find the hours worth automating or wire up workflows you've already mapped — pick the path that fits.
"We know something's off but we're not sure where to focus first."
Walk away with: a revenue/cost leak map, prioritized initiatives, a 30-day quick-wins playbook, and a 90-day roadmap.
Start with AI Audit →"We know the workflows. We need a senior team to wire them up — reliably, with guardrails."
Walk away with: a production automation with guardrails, audit logging, and a retained team for ongoing optimization.
Start with Intelligent Automation →The same three capabilities, every engagement. We diagnose first, unify the data, and build automation that stays fixed — so your team gets hours back, not more maintenance.
Most automation projects fail because they start with the tool. We start with the workflow, the data, and the dollars — so your budget goes toward the hours that actually matter.
TMS, WMS, ERP, support desk, BI, spreadsheets. We unify the data layer first, so every decision downstream sits on one number — not five tools and a Slack thread.
We build automation with observability, runbooks, and a clear owner for every flow. Nothing gets handed off and forgotten. It keeps paying off long after we're gone.
Every engagement follows the same arc: diagnose, automate, operate. Here's what that looks like in practice.
The problem: Inventory and fulfillment workflows spread across disconnected systems, manual reconciliation eating hours every week.
The approach: AI Audit → unify the data layer across TMS/WMS → automate reorder and exception handling.
The outcome: One source of truth for inventory across channels. Fewer manual touches, faster fulfillment, fewer stockouts.
The problem: Manual scheduling, billing coordination, and patient communication creating bottlenecks across clinical operations.
The approach: Map the end-to-end patient ops workflow → deploy agentic automation for scheduling, reminders, and billing handoffs.
The outcome: Coordination overhead drops. Staff time redirects from admin to patient care.
The problem: Support tickets manually triaged and routed. Escalation rules live in a wiki nobody updates. Resolution times climb.
The approach: Intelligent automation for triage, routing, and first-response. Escalation logic built into the system, not a runbook.
The outcome: Faster resolution without adding headcount. Agents focus on complex cases instead of sorting.
The problem: Month-end close and reconciliation consuming the finance team for a full week every cycle. Manual data pulls across systems.
The approach: Automate data extraction, matching, and exception flagging. Pattern recognition for recurring reconciliation issues.
The outcome: Close process shortens. Fewer manual touches, fewer errors, fewer late nights.
No tool pitches. No RPA vendor relationships. We start with your workflow and your P&L — and tell you honestly what's worth automating and what isn't.
The people who scope it build it. No handoffs, no juniors on your account. Strategy, design, and engineering from one integrated crew.
Automation needs owners. We build the runbooks, set up observability, and stay retained so nothing becomes next year's maintenance burden.
Audit timelines, system access, what you're not obligated to automate, and how fast the ROI actually shows up.
Three weeks for Focused (a single function), four weeks for Standard (cross-functional), and five to six weeks for Enterprise (multi-business-unit).
Read-only access is ideal. We sign your DPA, work inside your environment, and never move your data outside it.
Good. The roadmap explicitly tags which initiatives are people-only, process-only, automation-only, or AI-shaped. You pick what to do, in what order, and with whom.
The 30-day quick-wins playbook usually pays for the audit. Single-agent automations typically hit ROI in the first quarter; bigger orchestrations pay back in six to nine months.
Field notes from the studio — what we’re learning about AI products, agent UX, and the messy reality of shipping software in 2026.
