Automation · AI Workflows
Workflows that think.
Not just follow rules.
Traditional automation runs if-then logic. Ours calls ML models, handles exceptions intelligently, and adapts based on data. Built with n8n, Make, and custom Python.
Part of Automation services →
webhook trigger
POST /leads/inbound · fires in real-time
transform + validate
normalize, deduplicate, enrich
ML: score and routeAI
LangGraph decision node · classifies intent
qualified
crm update + notify rep
nurture
enroll in follow-up sequence
+ retry on failure · dead-letter queue · slack alert if all retries fail
Beyond simple automation
What happens when the logic gets hard.
Zapier connects A to B. That's fine for simple tasks. But what happens when the data needs cleaning first? When the routing decision depends on 12 variables? When the workflow needs to retry with different parameters if the first attempt fails?
We build automation that includes ML decision nodes, intelligent error handling with retry logic and fallbacks, data transformation pipelines, and monitoring that alerts you before things break rather than after.
Tools we use
The right tool for the complexity level.
Primary orchestration. Self-hosted on your infrastructure, unlimited executions, custom code nodes for complex logic.
Cloud-hosted option when clients prefer managed infrastructure over self-hosting.
ML decision nodes, heavy data processing, and complex business logic that automation platforms can't express cleanly.
Durable, long-running workflows that survive process restarts, server failures, and multi-day operations.
Have a workflow that needs more than Zapier?
Tell us the trigger, the logic, and what actions need to fire. We scope it after a free call.
Featured project
Related services
From the blog
Have a workflow that outgrew Zapier?
Tell us the trigger and what it needs to do. We'll scope the build.
Start an automation project