Workflow Automation that a human can audit.
Build · 3–6 weeks · fixed priceReplace the manual work that's been eating hours — handoffs, copy-paste, status chasing — with automation that runs quietly, logs clearly, and hands control back when something is wrong.
Most “AI projects” should have been an automation project first.
A handful of repeated workflows are eating disproportionate time. They rarely show up in headcount discussions until they hurt.
A sequence of Zapier-style hops, half-broken integrations, and one Google Sheet that nobody is allowed to touch.
When something fails, you find out from the customer, not the system. There's no log, no replay, no audit trail.
A complete, owned automation — not a script tied to one person's laptop.
- Workflow design
- End-to-end mapping with explicit human checkpoints, retries and exceptions
- Implementation
- Built on your stack first; custom Node / Python services only where they earn their keep
- Observability
- Structured logs, per-step traces, alerting on regressions — not just on crashes
- Idempotency
- Replays don't double-charge customers, double-send emails, or duplicate work
- Handover
- Documented system, runbook, and a 30-day care window if you want one
A quieter operations week.
The hours your team was spending on the workflow stop showing up in their week.
When something is wrong, the system says so, with enough detail for a human to fix it confidently.
Often the first build after the audit.
AI Audit
Almost every workflow build starts with an audit. Scope from data, not from hunches.
/services/llm-integrationLLM Integration
Once a workflow is reliable, LLMs can be wired into the seams where judgement is needed.
/services/custom-ai-agentCustom AI Agent
For a bounded job inside a workflow, an agent can take ownership of one step end-to-end.
Tell us which week is the loudest.
We'll start with an audit to size the work honestly, then build the system that quiets it down.