Automation
AI-Native Automation
AI-native automation goes beyond if-this-then-that. Pipelines understand unstructured inputs (emails, PDFs, chats), make decisions within rules you set and hand off exceptions to people, saving hours every week.
Core
PipelinesDocument AIScheduling
Also in the toolbox
Python workersCelery / RQCron & queuesOCRClaude / GPTn8nAirflowWebhooks
What you get
Deliverables, not just hours.
01Process mapping & automation roadmap
02Email / document intake pipelines
03Classification, extraction and routing
04Exception queues for human review
05Scheduled reports and summaries
06ROI tracking on hours saved
Typical use cases
Where this creates value.
Inbox automation
Read, classify and route incoming emails and attachments to the right system.
Back-office
Invoice processing, data entry and reconciliation handled end-to-end.
Reporting
Daily or weekly AI-written summaries from your databases and tools.
Related work
Automation in practice.
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