AI consultancy
AI consultancy and integration for real business processes
We help businesses work out where AI is genuinely useful, then build it into the tools and processes you already use. Practical advice first, integration second. Based in Wakefield, West Yorkshire, working with businesses across the UK.
Where AI tends to help, and where it doesn't
Most useful business AI today works with text, documents and repetitive decisions. It is strongest when a person can check the result, and weakest when it is trusted blindly.
Often a good use of AI
- Drafting and summarising emails, reports, proposals and meeting notes
- Sorting and routing incoming enquiries, tickets or documents
- Pulling information out of documents such as forms, invoices and contracts
- Answering questions from your own knowledge base, policies or product information
- Customer support assistants that hand over to a person when needed
- AI features inside your own software or app
Treat with caution
- Decisions with legal, financial or safety consequences made without human review
- Tasks that need guaranteed accuracy and have no practical way to check the output
- Sensitive personal data sent to tools without a suitable agreement in place
- Projects that start with "we need AI" rather than a process that needs improving
Consultancy and integration: what you get
Typically included
- Workshops to map your processes and find time-consuming, repetitive work
- A shortlist of opportunities, weighed by value, effort and risk
- Guidance on data protection and a simple AI usage policy for your team
- A proof of concept tested on real, appropriately anonymised examples
- Integration with the systems you use, such as your CRM, helpdesk, website or document storage
- Testing, monitoring and human review steps built into the workflow
- Training so your team knows how to use it and when not to trust it
Not included
- Usage fees charged by AI model providers, which depend on how much the system is used
- Legal sign-off on compliance, which should come from your legal adviser
- Guaranteed savings figures before the work has been tested on your processes
- Custom machine-learning research, which is scoped separately where existing models are not suitable
How an AI engagement runs
1. Map
We look at how work flows through your business and where time is lost, starting with the people who do it.2. Prioritise
We agree the one or two opportunities with the clearest value and manageable risk, and start there.3. Prove
We build a small proof of concept and test it on real examples, so you can see how well it works before investing further.4. Integrate and train
We connect it to your systems, add checks and monitoring, and train your team. Then we review how it is performing.
What affects the cost
Cost depends on the number of processes involved, how much preparation your data needs, how complex the integrations are and how much testing a use case requires. Ongoing model usage fees are separate and scale with use. Talk to us about a scoped first step.
If you are weighing up hiring versus outside help, read in-house vs outsourced development. If you are building a product with AI coding tools, read AI app builders vs custom development.
Frequently asked questions
What does an AI consultant actually do?
An AI consultant helps you find where AI will save time or improve a service, works out the risks, and plans how to introduce it. We also do the integration work, connecting AI models to the systems and data you already use, and help your team use it well.
Is it safe to put our business data into AI tools?
It depends on the tool, the agreement you have with the provider and the data involved. Consumer chat tools and business or API plans can handle data differently. Part of our work is agreeing what data can be used where, writing a simple usage policy for staff and considering your UK GDPR obligations.
Do we need to build our own AI model?
Usually not. Most business uses are better served by existing models, given the right instructions, your own documents to draw on and checks on the output. Training a bespoke model is a specialist project that only makes sense in particular circumstances, and we will say so if it does.
How do we know whether the AI is getting things right?
We test it against real examples before it goes live, agree what "good enough" looks like, keep a person in the loop where mistakes would matter and monitor results once it is running. AI output should be checked in proportion to the risk of it being wrong.
Should we build AI capability in-house or bring in outside help?
A practical approach is to use outside help to find and prove the first use cases, then decide what to bring in-house once you know what you need. Our in-house vs outsourced development comparison sets out the trade-offs.
Related services and guides
Services that often go with this one
- SaaS Development
Subscription software built to run as a business: user accounts, roles, billing, admin tools and integrations.
- Fix Vibe-Coded Apps
Audit, secure and stabilise apps built with Lovable, Bolt, Cursor, Replit and other AI coding tools.
- MVP Development
A first version of a new product, scoped to the smallest set of features that lets real users test the idea.
Costs, comparisons and examples
- In-house vs outsourced development
Cost, control, hiring and risk compared.
- AI app builders vs custom development
Lovable, Bolt, Cursor, Replit and v0 compared with a custom build.
The Lilybank Agency is based in Wakefield, West Yorkshire, and works with businesses across the UK. See all our services, browse the portfolio, read our case studies or see the areas we serve.
Talk to us about your project
Tell us what you need and what you already have. We will get back to you within one working day to talk through scope, timings and budget.