services / AI & Automation 三
Automation that earns its keep.
who it’s for 誰
Teams buried in repetitive work — support triage, quoting, data entry, content operations — who want it handled automatically rather than merely assisted.
What we do
We automate specific, measurable workflows rather than announcing an AI strategy. Each engagement starts by finding where the hours actually go, then building the smallest system that removes them.
How a build runs
We map the workflow and its failure modes, build the pipeline with logging and fallbacks, then run it against real historical cases before it goes near a customer. Evaluation is part of the deliverable, not an afterthought.
Where this goes wrong elsewhere
Most failed AI projects skip the boring parts — evaluation, fallbacks, cost controls. The model is rarely the problem. The absence of someone deciding what should happen when it is uncertain usually is.
what you get 得
- Custom AI agents — OpenAI, Anthropic
- LLM and RAG implementations over your own data
- Customer support autopilot
- Data processing pipelines
- Workflow automation — CRM, GHL
- Monitoring, fallbacks and evaluation
built with 具
questions 問
- What separates a real AI build from a demo?
- Fallbacks, evaluation and monitoring. A demo answers the happy path. Production handles a bad retrieval, a rate limit, an ambiguous input and an upstream outage without a human noticing — and you can see how often each of those happens.
- Can it read our own documents and data?
- Yes — that is what RAG is for. We index your content into a vector store so answers are grounded in your material rather than the model's general knowledge, which is also what keeps it from inventing things.
- Where does automation usually pay off first?
- Wherever the same decision is being made repeatedly from the same inputs: first-response support, lead qualification, quoting, order status, routine data movement. We audit the workflow before building so the automation targets the actual bottleneck.
- What happens when the model gets it wrong?
- Anything consequential routes to a human. We define the confidence threshold and the handover path up front, so automation reduces load instead of moving risk into the customer's lap.
often paired with 連