AI Engineering Studio
We help growing businesses automate the right workflows — and build the AI to run them in production.
LotusNex helps operations and engineering leaders identify which repetitive processes are worth automating — and builds the production AI systems to run them safely. Process-first. Architecture-first. Built to operate — by your team or ours.
Workflow automation · AI security · Production reliability
Sound familiar?
You know which workflows should be automated. You're not confident they're actually ready.
The candidates are obvious — document review, data re-entry, report generation. What's less obvious is whether your processes are consistent enough, your data accessible enough, and your systems connected enough to make automation work without creating new problems.
It works in your demo. Real users are a different story.
Your AI feature impresses in controlled conditions. With real users, real data, and real edge cases, it hallucinates, breaks, or fails silently — and you don't have the visibility to know until something downstream goes wrong.
You're live. But costs are climbing, errors are quiet, and you're not sure why.
The system is running. Token spend keeps drifting upward. Edge cases surface as customer complaints rather than alerts. You don't have a clear line from a bad output back to the decision that caused it — and that gap is getting harder to ignore.
This is the moment we're built for.
We've built document extraction pipelines for professional services firms, permissioned retrieval systems for regulated SaaS platforms, agent orchestration with human approval gates for operations teams, and security hardening for AI systems already in production.
See our work →How we work
Every engagement starts with process and architecture — defining what to automate, how it will fail, and what it takes to operate it before a line of production code is written.
Before you engage
Workflow Discovery — free, 12 questions, 1 business day. You get a Workflow Readiness Score and an Efficiency Dividend: the dollar case for which workflows to automate first.
1–2 weeks
1) Audit
- Target workflows mapped against production constraints
- Evaluation criteria and success metrics agreed upfront
- Failure modes defined before any code is written
You get: a scoped build plan — or an honest "not yet."
4–8 weeks
2) Build
- Agents, pipelines, and integrations built to spec
- Evaluated against real data throughout — not just at the end
- Milestone checkpoints with your team — no black-box delivery
You get: a running system that holds up under real inputs.
2 weeks + optional ongoing
3) Harden & Own
- Observability and alerting live before go-live
- Guardrails and approval flows validated
- Runbooks written for the people who operate it
You get: a system your team owns and can operate — or we stay involved on your terms.
The first step is the Workflow Discovery.
12 questions. Results immediately. Free — whether we work together or not.
We work with 2–3 companies at a time. Current intake: open.