Strategic planning
Every project begins with an audit of the process and a number agreed in writing, so we build against a target, not a demo.
At NeuroHub, we are committed to empowering your digital vision with automations tailored to your unique needs. Our team of skilled engineers, coupled with proven tooling, ensures that we deliver systems that keep running long after launch.
Every project begins with an audit of the process and a number agreed in writing, so we build against a target, not a demo.
We tailor every automation to the systems you already run, resulting in solutions your team keeps using.
Our projects are designed for the people who operate them, prioritising clear handovers and intuitive interfaces.
We adhere to strict timelines and project schedules to ensure delivery without compromising on quality.
An assistant that reads the shipment system and answers customers itself, instead of routing every question to a person.

The catalogue moved to static rendering, so the pages that carry the traffic stopped waiting on the server.

A site where half the catalogue was invisible to crawlers, fixed in the order that put traffic back fastest.

The AI assistant resolves two thirds of tickets before a person sees them, and the handover to an agent is clean. We measured it weekly with them and the numbers held.
Sarah Thompson
COO, logistics operator
Core Web Vitals went green on every template and organic traffic recovered within a quarter. The team explained every trade-off before making it.
Wade Warren
Head of e-commerce
They said no to two ideas we had and were right both times. What they did build has been running for a year without us touching it.
Lisa Williams
CEO, HealthTech startup
Our own engineers picked the project up in a week. Prompts, evaluations, tracing — all there, all explained.
Jennifer Lee
CTO, B2B services
A single well-scoped automation typically runs four to eight weeks from kickoff to production. An AI feature inside an existing product with real integration work runs eight to sixteen weeks. The biggest variable is how many systems we have to touch, not the AI itself.
Yes. Everything runs on your accounts and your infrastructure, and the repository is yours from the first commit — source, prompts, evaluation sets and documentation included. We are happy to stay on for support, but nothing is built so that you have to keep us.
Inference is usually the smallest line: a support agent handling ten thousand conversations a month typically lands in the low hundreds of dollars. Budget fifteen to twenty-five per cent of the build cost per year for maintenance, which covers failure reviews, prompt updates and model migrations.
We work inside your infrastructure and your data boundaries, use providers with zero-retention terms where required, and can deploy against self-hosted or regional model endpoints when regulation demands it. Data handling is agreed in writing during scoping, before any build starts.
We will say so. Part of the audit output is a list of processes that should not be automated yet — because the rules are not clear, the volume is too low, or classic software solves it more cheaply. Those lines are often the most valuable part of the engagement.