Automations & workflow integration
Automations and workflows that replace repetitive work
Custom business automations that quietly remove hours of weekly email, spreadsheet, and copy-paste work. Built, monitored, and handed over — no black-box SaaS rental.
What you get
- A scripted or scheduled automation, running on your own infrastructure on a predictable cadence.
- Monitoring and alerting wired up — you hear about failures through Slack or email, not from a customer.
- A human-readable runbook covering what the automation does, how to pause it, and how to re-run it.
- Logging that makes it obvious which records were touched, when, and what changed.
- A clear rollback path for the cases where an automation needs to be undone in a hurry.
- Source code in your GitHub, with secrets in your own vault — never ours.
- A handover call and a two-week monitoring window so your team is comfortable before we step back.
Who this is for
The first group we help is small and mid-sized businesses bumping into the ceiling of Zapier, Make, or n8n. The workflow started simple, grew to twelve steps, and now breaks in ways the no-code platform won't debug. The monthly bill has quietly doubled. Sensitive data is flowing through a vendor that shouldn't see it. The right answer is usually to pull the critical pieces back in-house and keep the platform for the genuinely simple parts.
The second group is teams spending real hours each week on repetitive email, form, and spreadsheet work — the weekly billing reconciliation, the new-customer onboarding checklist, the “pull the report, email the client” loop. You don't need a rebuild, you need the robot that should have been written a year ago. We find the two or three steps eating the most time and automate them first.
How we approach automations
- 1
Map the real workflow
We start by watching the manual process end to end — the emails, the spreadsheet columns, the Slack pings, the “and then Mike checks it.” The map we draw on day one almost never matches the one-liner in the kickoff call, and that's usually where the useful work hides.
- 2
Identify the 20% eating 80% of the time
Most workflows have two or three steps that quietly consume the majority of the effort. We name them, agree on which ones to automate first, and set aside the rest. Shipping a focused automation fast beats scoping a perfect one forever.
- 3
Script carefully — idempotent, logged, safe
We write automations that can run twice without duplicating work, that log enough to debug at 9am on a Monday, and that fail loudly instead of quietly. Destructive steps get confirmations or soft-deletes. The goal is zero surprises.
- 4
Monitor the first two weeks, then hand over
After launch we watch the automation in production, tune the alerts, and fix the edges nobody predicted. Then we write the runbook, do a walkthrough, and step back. You own the code, the schedule, and the pager.
What makes our approach different
Simple, sane engineering
Most automations don't need a workflow platform or a distributed queue. We reach for cron and a Postgres table first, and only add complexity when there's a real reason.
No vendor lock-in
Your automation lives in your GitHub and your cloud. We don't run it on a Bluestone server you'd lose access to if we parted ways tomorrow.
We don't add AI unless it actually helps
Plenty of “AI automation” is a regex with a markup. We use LLMs where they genuinely handle messy inputs — classifying unstructured email, summarizing long threads — and we skip them everywhere else. No AI theater.
Flat, predictable pricing
We scope the workflow and quote a flat fee. No per-run charges, no seat fees from us, and no surprise invoices when the automation runs more than we expected.
Tech we reach for
Most automations we build run on Node and TypeScript, with Python for data-heavy jobs. Scheduled work usually runs as cron on Vercel or Railway; longer, multi-step workflows that need retries and durability sometimes run on Temporal. Postgres handles state and audit logs. For LLM-assisted steps we stay model-agnostic and keep prompts, inputs, and outputs logged. We pick the simplest thing that safely solves your problem, and we avoid adding any service your team can't cancel or log into on their own.
Common questions
Why not just use Zapier?+
For a handful of simple triggers, Zapier or Make is usually the right answer and we'll tell you so. We get hired when the workflow has outgrown that — conditional logic the no-code platform handles awkwardly, a monthly bill that's quietly become large, data that shouldn't leave your infrastructure, or a failure mode that Zapier won't debug for you at 2am.
What if the automation breaks?+
Everything we ship has monitoring and alerting wired up from day one. When something fails you get a Slack or email message with enough context to triage, plus a runbook covering the common recovery steps. For the first two weeks after launch we watch production alongside you before stepping back.
Do you automate everything with AI now?+
No. We use LLMs when they earn their keep — pulling structured data out of messy email, classifying support tickets, summarizing long threads — and we skip them for anything a small script handles better. An AI step adds cost, latency, and unpredictability, so it has to pay for itself.
Can you automate [specific tool]?+
Usually yes. We regularly automate workflows across HubSpot, Salesforce, Stripe, Shopify, QuickBooks, Gmail, Google Drive, Notion, Airtable, Slack, and custom in-house systems. If the tool has an API or webhook, we can almost always wire it in. If it doesn't, we'll say so clearly.
What's the typical project size?+
Most automation projects land between roughly $8,000 and $30,000 as a flat fee, depending on how many systems are involved and how much business logic sits in between. A single focused workflow can be less; a full operations rework that chains a dozen automations together is more. We quote a fixed number up front.
Ready to automate the work nobody should still be doing by hand?
Tell us what the workflow looks like now. You'll talk to Eric directly and get an honest read on whether it's worth automating, what it would cost, and where a no-code tool would actually do the job better. No pressure.
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