Services · AI & Automation

AI that earns its place in your operations.

Custom machine learning, LLM-powered features and workflow automation — built feasibility-first, evaluated against your real data, and designed around the humans who'll use them. No AI for AI's sake.

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We drink our own champagne

We run our own business on this.

Before we sell AI automation, we build it for ourselves. Novanexom's own sales operation runs on AI agents and automation pipelines we engineered in-house — so when we scope your project, we're speaking from production experience, not slideware.

AI lead-scoring agents ranking thousands of prospects
Automated outreach pipelines built on n8n and LLM APIs
Internal AI tools for email, follow-up and research workflows
The same evaluation discipline we apply to client models

How we engage

Feasibility first. Always.

AI projects fail when ambition outruns evidence. Ours are structured so the evidence comes first.

Feasibility study

We test whether your data can actually support the outcome you want — a short, fixed-scope engagement with an honest answer at the end, including "no."

Build & evaluate

The model or automation is built and measured against your live data, with quality gates agreed up front — accountability built into the commercial terms.

Production & iterate

Deployment, monitoring and continuous improvement — AI that keeps earning its place after launch, not a demo that decays.

Proven in production · Industrial AI

95% forecast accuracy, 5–60 minutes ahead.

For a German waste-management technology company, we built a custom time-series model predicting calorific and steam values — proven against live data under success-based terms before the engagement progressed.

Read the case study →

FAQ

Honest answers, up front.

How do I know AI will actually work for my use case?

You don't — and neither do we, until we've seen your data. That's exactly why we start with a short feasibility study instead of a big commitment. If the data can't support the outcome, we'll tell you so, and you'll have spent a fraction of a full project finding out.

What does an AI automation project cost?

It depends entirely on scope, which is why we won't quote a number before understanding the problem. The feasibility study is deliberately small and fixed-scope; the build phase is quoted only after we know what we're building. Where it makes sense, we offer success-based structures where part of our fee is contingent on agreed quality gates.

Is our data safe with you?

Data handling terms are agreed before any data moves — NDAs, access controls, and processing limited to the engagement's purpose. For LLM-based work we use API configurations that don't train on your data, and we'll walk you through exactly where your data goes.

How long does a feasibility study take?

Typically a few weeks, depending on data readiness. The output is a clear answer: what's achievable, at what accuracy, and what a production build would involve — in plain language, not a research paper.

Can you automate our sales or back-office workflows specifically?

Yes — it's the automation category we know most intimately, because we run our own outbound sales on AI agents and n8n pipelines we built ourselves. Lead scoring, enrichment, outreach drafting, follow-up sequencing and reporting are all automatable today.