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Most teams don't lack AI ambition. They lack execution. We integrate LLMs and automation directly into your existing tools and workflows, so the output is a production system your team actually runs, not a slide deck.
We start with a workflow audit to find where automation actually pays back fastest, then integrate directly into your existing tools rather than building a parallel system nobody adopts. The deliverable is a production pipeline your team runs, with iteration support afterward, not another proof of concept.
Both, matched to the risk level of the task. Low-stakes, high-volume work (data entry, reporting, triage) is a good fit for fully agentic pipelines; anything touching money, compliance, or customer-facing decisions typically keeps a human approval step by design.
Most engagements plug into your existing stack (n8n, Zapier, Make, or a custom Python/LangChain pipeline) rather than replacing it. We map integration points during a short audit before any build work starts.
A 20-minute build call: no deck, no pitch. Just your idea, our honest read on scope, and a fixed-price plan if it's a fit.