Expertise in applied AI
NeuroHub builds on models and tooling that hold up in production, so every automation you get is measurable, maintainable and ready for what comes next.
AI automationStart a projectThat drives growth
We build AI agents, automations and custom software that remove manual work from your operations — shipped in weeks, measured in hours saved.
Clients
60+
Projects
120+
Happy clients
100%
Automations
400+
Years of experience
5+
Reasons to choose NeuroHub for your digital journey
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Proven track record of delivery
From a first automation to a full AI layer over an operations team, our projects ship on time and keep running long after the handover.
Client-centric approach
At NeuroHub we start from your process, not from a technology. You see every decision, every number and every trade-off before it is made.
Dedicated team of engineers
Our engineers, designers and analysts bring years of work in operations, delivering scalable, secure and well-documented systems for your business.
What we do
Assistants, bots and automations that take the repetitive half of your operations off people.
Starts from $1,900
Search work judged by qualified traffic and revenue, not by positions in a monthly report.
Starts from $3,100
Landings, corporate sites and stores built to load fast, rank well and be edited without a developer.
Starts from $1,500
Front-end, back-end and web applications, written so the next engineer can pick them up.
Starts from $1,200
Our works
All worksCategoryAI & AutomationYear2026
An assistant that reads the shipment system and answers customers itself, instead of routing every question to a person.
CategoryWebsite DevelopmentYear2026
The catalogue moved to static rendering, so the pages that carry the traffic stopped waiting on the server.
Testimonials
All testimonialsNeuroHub took a month of manual work off our support team.
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
A rebuild that actually got faster, not just prettier.
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
Working with NeuroHub was a pleasure.
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
The first agency that handed over documentation we could use.
Our own engineers picked the project up in a week. Prompts, evaluations, tracing — all there, all explained.
Jennifer Lee
CTO, B2B services
Frequently asked questions
View allHow long does a first project take?
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.
Do we own the code and the infrastructure?
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.
What does it cost to run after launch?
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.
How do you handle sensitive data?
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.
What if AI turns out to be the wrong tool for our process?
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.