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AI Automation

AI Automation & Agentic Workflows

We build automation that removes repetitive engineering work. That means custom pipelines, agentic workflows, and retrieval systems. It is software written for your process, not a no-code template.

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You probably know this is broken if…

  • Repetitive engineering and ops work
  • No-code tools that almost fit
  • AI experiments that never reach production
  • Manual processes that do not scale

What's inside

  • Custom Python automation pipelines
  • Claude Code plugin and slash-command development
  • Retrieval-augmented knowledge bases (Qdrant and Postgres)
  • LLM workflows for content and data
  • Multi-step agentic automations
  • Integration with your existing stack

How it works

  1. 1Map. We find the repetitive work worth automating, and the work that should stay with people.
  2. 2Prototype. We build a working pipeline and test it against real inputs. We use Claude Code, Python, and retrieval where they earn it.
  3. 3Ship. We deploy the automation into your stack with logging and guardrails so it can run unattended.
  4. 4Measure. We track what it saves and tune it. The automation should pay for itself.

Recent work

We built a Claude Code plugin with a local retrieval knowledge base on Qdrant and Postgres. We also run a daily job-search pipeline on AWS. Both are in real use.

See selected work →

Automate the work you should not be doing.

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Built for your process, and yours to keep.