About

We got tired of watching good people do machine work.

We build custom AI automation for businesses of any size, and ship our own AI products. Both come from the same conviction: most of what a company calls work is a rule waiting to be written down.

The Fluxera AI Labs team working through a client process map

How we got here.

We kept seeing the same thing: companies paying skilled people to move data between systems that could have talked to each other. Not by design — nobody had ever sat down and mapped it.

The tools were never the problem. Every company already owned more software than it used. What was missing was the layer between them.

That work led to our own software. Solving hard, latency-bound problems taught us things that became products — Fluxera 5.0 came out of that, with three more following.

Today we take automation engagements across any industry, build marketing systems that execute a real strategy, and ship our own products.

What we believe

Four positions we hold.

They decide what we take on and what we turn down, so it is fairer to say them out loud.

Custom beats configured.

Generic tools get abandoned because they can't handle exceptions — and every real business is mostly exceptions. We build around them.

Mapping is the work. Building is the easy part.

Projects fail because someone automated a process nobody had actually understood — usually including the people running it.

You should be able to fire us.

Open, portable tooling, documented as we go. A trapped client eventually resents you. We would rather earn the next engagement.

Silent failure is the real risk.

An automation that fails loudly is an inconvenience. One that quietly produces wrong output is a serious problem. Everything we ship monitors itself.

Capabilities

What we're actually good at.

A short list on purpose. Everything here is something we have shipped and supported, not something we would be willing to try.

Workflow engineering
n8n at production scale — custom nodes, queue mode, error handling, self-hosted deployment.
Applied model integration
Selecting and integrating models per task, with the fallback and cost-control layer around them.
Marketing strategy
Positioning, channel selection and funnel design — so the automation has something correct to execute.
Real-time inference
GPU-side optimisation for latency-bound work. Where Fluxera 5.0 came from.
Systems integration
Connecting systems that don't want to be connected: legacy APIs, no APIs, portals, spreadsheets, email.

Tell us what's manual.

The first call is a process walkthrough, not a pitch. Bring the thing your team complains about most.

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