1–3 wks
Per focused workflow, scoped up-front
Service · Workflow Automation
Automation that can make judgment calls.
Zapier is great for plumbing — but plumbing doesn't read contracts, triage tickets, or approve refunds. We build workflow automations with AI in the loop: the if-this-then-that logic where "this" is a judgment a human used to have to make.
50+
SaaS tools we regularly integrate
Full logs
Observability + alerting on every run
Your infra
Self-hosted or serverless — your call
01 — The opportunity
Most "automation" is still stitching tools together.
A Zap that fires when a form submits. An integration that moves rows from one sheet to another. Useful, but shallow — all the judgment still lives with humans. Someone still has to read the incoming email and decide: refund, escalate, or ignore? Someone has to look at the invoice and route it to the right approver. Someone has to check if this support ticket is a known issue.
With AI in the loop, those judgment steps become part of the workflow. The automation reads, decides, acts, and only involves a human when the model is unsure or the stakes are high. You get leverage without losing control.
02 — What we automate
The patterns we ship most.
- Inbound triage. Every incoming email, form submission, or support ticket gets read, classified, routed, and — when safe — resolved automatically. Refund requests, partnership inquiries, bug reports, sales leads. Human review only on edge cases.
- Approval routing. Invoices, contracts, discounts, refunds. The automation applies your policy ("under $500 auto-approve, over $5k CFO sign-off"), routes the exceptions to the right person, and tracks the audit trail.
- Data enrichment & cleanup. New leads, new accounts, new hires — the automation pulls public data, normalizes formats, flags duplicates, and writes clean records back. No more "reconcile the CRM once a quarter" projects.
- Multi-step orchestration. Onboarding flows with 15 steps across HR, IT, Slack, Google Workspace, and benefits platforms. Offboarding that actually offboards. Status updates that keep every stakeholder in sync.
- Notification & report generation. The system watches your data, writes the narrative, and posts it where it matters — Slack, email, exec dashboards. Daily pipeline digests, weekly ops reviews, monthly board packs.
03 — Stack choices
n8n, custom code, or both.
For simple workflows without AI, Zapier and Make are fine — we'll tell you if that's the right call. For AI-heavy workflows or anything with sensitive data, we lean on n8n (self-hosted, open-source) or write custom code on Cloudflare Workers, AWS Lambda, or your cloud of choice. The right tool depends on complexity, cost, and data residency.
We often ship hybrids: n8n for the plumbing (triggers, CRM writes, Slack notifications) with custom code for the AI-heavy steps (classification, drafting, reasoning). You get the speed of low-code where it fits and real engineering where it matters.
04 — Observability
Every run visible, every failure caught.
Automation without observability is a liability. Everything we build ships with a run history UI, structured logs, and automatic alerts (Slack or email) when a run fails or an AI step returns low-confidence output. When something breaks, you see the exact input, the exact output, the exact step that failed — no spelunking.
FAQ
Common questions.
How is AI workflow automation different from Zapier?
Zapier is if-this-then-that: a trigger fires a fixed action. AI workflow automation handles judgment: read this email and decide whether it needs a human or can be auto-resolved; look at this invoice and approve, reject, or route for review; read this contract and flag anything that deviates from policy. Zapier is great for plumbing. AI automation is for the work that used to require a human's eyes.
Should we use Zapier / Make / n8n, or build custom?
Start with Zapier/Make/n8n for simple flows. Move to custom when: the workflow has 6+ steps, the cost scales unfavorably, you need complex conditional logic, you're moving sensitive data you don't want on someone else's infrastructure, or an AI model needs to make a call that affects downstream steps. We often build hybrids — n8n for plumbing, custom code for the AI-heavy steps.
How long does a typical automation project take?
A single focused workflow — say, invoice approval routing — ships in 1–3 weeks. A broader orchestration effort (5–10 workflows across a department) runs 4–10 weeks. We scope each workflow individually so you can stop between them and assess the ROI.
What about observability and debugging?
Every workflow ships with logs, a run history UI, and Slack/email alerts on failures. When something goes wrong, you see exactly which step failed, what the input was, and what the AI thought. No black boxes.
Who maintains the automations long-term?
Your team, with documentation we deliver on day one. We also offer optional retainers for ongoing changes, new workflows, and model updates. But you're not locked in — everything runs on your infrastructure with your API keys.
What tools do you integrate with?
Salesforce, HubSpot, Gmail, Google Workspace, Microsoft 365, Slack, Notion, Airtable, Linear, Jira, Intercom, Zendesk, Stripe, QuickBooks, DocuSign, Greenhouse, and basically anything with an API or webhook. If it doesn't have an API, we can often work with the UI directly using browser automation.
Got a workflow that's killing your team?
We'll scope it in a 30-minute call.
Describe the process. We'll tell you whether it's a 1-week Zap, a 3-week AI workflow, or something that needs real software — and give you honest ROI math.
Start the conversation →