AI Integration & Consultancy UK

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In short

Practical AI integration and consultancy. AI connected to your systems and your data, governed by approval steps you control, with honest advice first about where it pays back and what to leave alone.

Past the experiments

Most businesses have tried AI tools. Far fewer have AI working inside their systems, with their data, under their rules. That gap is where the value sits and it is engineering work rather than magic.

Your data, your rules

Priority Pixels builds AI into business workflows. Assistants connected to your own systems so answers come from your data. Document and content generation governed by your brand rules and approval steps. The pattern is always the same. AI does the routine work and your team approves it.

Honest advice first

Consultancy comes before integration. A short engagement maps where AI genuinely pays back in your business, what your data supports today, what the risks are and what to leave alone. You get a plan with priorities rather than a pitch.

AI delivered by a senior team that uses it every day

AI runs through our own agency workflows every day, so the guidance you get from Priority Pixels comes from operating AI in production rather than from a slide deck. We know where AI saves real hours, where it needs a person keeping the final say and where the honest answer is not to build anything at all.

Governance rules agreed in writing
Data handling designed per project
Human approval steps built in
Grounded in your own systems and data
Measurable hours back per workflow
Monitored under agreed support
Rollback available at launch
Consultancy before any build

Every AI workflow we ship is governed by rules you set. What goes to an AI platform, what stays inside your systems and what is logged are agreed in writing before a build starts, and approval steps are built in so nothing customer facing goes out unattended.

Priority Pixels team working on an AI integration project

Our AI integration services

Practical AI workflows built inside the systems you already run and governed by the rules you set. Below are the AI use cases we deliver most often for our clients, with a person keeping the final say on anything customer facing.

Meeting summaries and action write-up

Every meeting captured, summarised in your voice and posted to the right record. Actions written up against the right person and deadlines flagged, saved back to your CRM without anyone typing it up.
Works with
- Teams
- Google Meet
- Zoom
- HubSpot
- Salesforce
- Pipedrive
- Asana
Enquiry triage and routing

Inbound emails, form fills and helpdesk tickets read, classified and routed to the right person with a written summary attached. Reduces first response time and stops routine questions landing in the wrong inbox.
Works with
- Microsoft 365
- Google Workspace
- HubSpot
- Freshdesk
- Zendesk
Document drafting under your rules

Proposals, quotes, contracts and reports drafted from a short brief and your templates, checked against the wording rules you set. A person keeps the final say on every document that leaves the office.
Works with
- Microsoft 365
- Google Workspace
- SharePoint
- OneDrive
- DocuSign
Data extraction from documents

Invoices, forms, timesheets and contracts read automatically, with the fields you care about pulled into your accounting, project or CRM system. Removes the manual typing step where errors and delays creep in.
Works with
- Xero
- QuickBooks
- Sage
- HubSpot
- Salesforce
Reports written from your data

The weekly and monthly reports someone builds by hand, generated from the systems the numbers already live in and drafted in your voice. You review the final report and send it out.
Works with
- Microsoft 365
- Xero
- QuickBooks
- Stripe
- HubSpot
- Salesforce
AI readiness consultancy

A short paid engagement mapping where AI genuinely pays back in your business, what your data supports today and what to leave alone. You get a written plan with priorities, not a pitch.
Includes
- Discovery
- Data audit
- Priorities
- Written plan

Meet the team

The team who deliver Priority Pixels AI workflows. AI runs through our own operations every day, so the guidance you get comes from people who use these tools themselves.

Owen Lewis

Senior Web Developer

Owen leads every software build. He scopes the technical approach, owns the architecture and reviews everything that ships, from first commit to launch.
Lisa Moody

Website & SEO Support

Lisa builds alongside Owen and looks after the software once it is live. Updates, monitoring and the support requests that need a developer rather than a script.
Monica Johnson

Senior Designer

Monica designs the interfaces. Portals and applications that make sense to the people using them without a training manual.
Jess Pearce

Digital Marketing Administrator

Jess coordinates delivery. Progress updates, scope decisions logged in writing and the client-side communication that keeps a build moving.

Sectors we work with

Different sectors need different AI use cases. We build practical workflows against your systems and your rules, whether that is triaging enquiries for a healthcare provider or drafting proposals for a professional services firm.

AI readiness consultancy

A short paid engagement mapping where AI genuinely pays back in your business, what your data supports today and what to leave alone. Consultancy comes before any build because most businesses do not need every AI use case they have heard of, and some need none of them at all. You get a plan with priorities: which processes AI would save real hours on, which are not ready yet and which are honestly better left to a person. Some of the honest answers are about what not to build, which is often more valuable than a pitch.

Governance and data handling

What goes to an AI platform, what stays inside your systems and what is logged are all agreed in writing before a build starts. Every AI workflow includes a governance document that covers data classification, prompt handling, model selection and retention. Approval steps are built in so nothing customer facing goes out unattended. If your industry has regulatory constraints (healthcare, financial services, legal), those constraints are named and designed around before any code is written. AI runs under rules you set, not rules the model decides for itself.

Workflow design with human oversight

Approval steps are built into every workflow. AI drafts, a person approves, nothing customer facing goes out unattended. Every workflow is designed around a specific business decision: what does AI actually do here, what does the person do and where is the audit trail. Prompts are versioned so every generation can be traced back to the exact prompt that produced it. Model outputs are logged with the input, so a review after the fact can catch drift, bias or errors before they compound into a problem you find out about from a customer.

Build and testing

Every AI workflow is built against your systems through their APIs, tested against real inputs and reviewed by a person before it goes live. Testing covers the happy path, the edge cases and the adversarial cases: what the model does when the input is deliberately unusual, ambiguous or out of scope. Retrieval augmented generation, where used, is tested against a documented question set so the answers are grounded in your data rather than the open internet. Every build is documented so anyone on your team can see how the workflow works and what data it touches.

Measurement and iteration

Every AI workflow is built against a measurable saving, so you can see what it replaced and what it returned. If the workflow was meant to save two hours per week on report drafting, the reporting says whether it did or did not. Adjustments are made as the models change and your business changes. Prompts, models and workflows are all versioned, so a change to any of them can be rolled back if it does not perform as expected. AI is a moving target and the review schedule built into every engagement reflects that reality.

AI integration and consultancy FAQs

The questions we hear most about AI integration, from choosing a platform to managing accuracy and owning your data.

Get in touch

Which AI platforms do you recommend?

The platforms that fit your systems and your governance needs. Recommendations are made in discovery and explained plainly, with controls set out before anything is built.

How do we know AI is the right answer for a given problem?

By starting with the problem, not the technology. Every AI engagement opens with a consultancy call that walks the process, identifies where the bottleneck actually is and asks whether AI is genuinely the fastest route to fix it. In some cases it is, and we say so. In others a simpler automation or a settings change is a better answer, and we say that too.

What about the risk of AI giving the wrong answer?

The risk is real and it is managed at design. Anything customer facing goes through a human approval step, so a person signs off before an AI generated response is sent. Anything internal is scoped against the source of truth, so answers cite the record they came from and staff can check them.

Who owns the data we put into an AI system?

You do. Every platform we recommend is chosen with data ownership, training use and residency written into the contract, so your data is not used to train third party models unless you explicitly agree to it. Where UK or EU data residency is required, we scope for a provider that supports it.

Do we need to change our existing systems first?

Usually not. AI workflows are built against the systems you already run through their APIs, and the consultancy confirms what your current setup supports before anything is proposed.

How do we start an engagement?

Every AI engagement starts with a consultancy call to understand where AI genuinely pays back in your business, followed by a written plan with priorities. If the plan makes sense, we scope any build that follows with cost and delivery dates before development starts. Get in touch through the contact form and we will book the consultancy call in.

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