Manual work is invisible until you add it up. A few minutes here, a recurring report there, an inbox someone triages by hand, and suddenly a third of your team's week is gone to work no human should be doing.
We're an AI automation agency that builds systems, not demos. We wire your tools together with n8n, add LLM reasoning with LangChain and OpenAI or Claude, and ground answers in your own data using RAG and vector databases. The result: workflows that run themselves and free your team for work that actually needs a human.
We start where the payback is fastest. Most automations we ship recover their cost in 2–3 months by removing 70–90% of a repetitive workflow, and they keep running long after the invoice is paid.
Of a manual workflow removed, so your team stops doing work an agent can do.
Typical payback period before the automation is saving more than it cost.
RAG over your own data means the AI cites your facts, not hallucinations.
We map where hours actually go and pick the workflow with the highest payback, not the flashiest demo.
We connect your apps, APIs, and databases into a reliable pipeline with retries and error handling built in.
LangChain orchestrates OpenAI or Claude, grounded in your data through a vector DB, so answers are accurate and auditable.
We track what the automation saves, add guardrails, and hand you a system you can trust and extend.
Proven tools, chosen for the outcome — not the resume.
See how this work has played out for teams we've shipped for.
Anything repetitive with a clear trigger and rules: lead routing, invoice and document processing, report generation, inbox triage, data sync between tools, and customer-support deflection with RAG. If a person follows the same steps every time, it's a candidate.
We use retrieval-augmented generation (RAG). The model answers from your own documents and data in a vector database, with citations, instead of guessing. We also add validation and human-in-the-loop checkpoints for anything high-stakes.
Both. n8n handles orchestration and integrations fast, and we drop into Python and LangChain wherever the logic needs real engineering. You get the speed of low-code with the reliability of senior code.
Most engagements we scope target a 2–3 month payback by removing 70–90% of a specific manual workflow. On the discovery call we estimate the hours your team currently loses to that workflow and weigh them against the build cost, so you see the payback math before you commit.
We build with retries, error handling, and monitoring, and we document every workflow so it's maintainable. You own the system and can extend it without us.