Vebryx

AI integration servicesAI that earns its place in your product.

We put AI to work where it pays off: inside the product you already have, or in a new one built around it.

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Not ready yet? See our work or read our guides.

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A developer working on code at a laptop

Case study

See it in action.

Bright, modern dental clinic with a white and teal treatment chair

Healthcare

Dentora

Practice management for dental clinics

One system for bookings, records and billing, saving up to 60% of time.

“Working with the team helped us move away from spreadsheets and multiple tools to a single platform that fits our clinic's daily workflow.”
Dr. Sarah Williams · Lead Dentist
Read the case study

AI Integration & Automation

Sound familiar?

Teams with real work to automate, or an idea that only works with AI.

Built your app with AI tools like Lovable or Cursor? See Prototype to Production

  • Your team spends hours on work a model could draft in seconds.
  • You've tried AI features, but they're unreliable or off-brand.
  • You don't know what's realistic, or what it costs to run.

See it work

AI at work in your tools.

Pick a job to see how AI moves through the tools you already use, and where you stay in control.

Slack
AI Agent

A new enquiry comes in

Example
  1. Reads the new enquiry in Gmail
  2. Finds the customer's history in HubSpot
  3. Checks your prices in Google Sheets
  4. Drafts a reply with prices and next steps
  5. You check the draftApprove
  6. Sends the reply from your inbox
  7. Logs the conversation in HubSpot

An example. We design each workflow around your tools and your rules.

What's included

Everything handled, end to end.

  1. 01AI auditA focused review that finds the tasks worth automating, and the ones that aren't.
  2. 02Answers from your dataAssistants and search that answer from your documents, with sources.
  3. 03AI features in your productDrafting, summaries, search, tagging and recommendations, built in.
  4. 04Workflow automationProcess documents, emails and tickets without the manual handling.
  5. 05Model integrationConnect the right model, or fine-tune one when it earns its keep.
  6. 06Guardrails & monitoringTesting, fallbacks and usage tracking so quality and costs stay in view.

Pricing

Start with an AI audit.

A clear first step: we find the work worth automating and price it, before you commit to a build.

  1. Step 1

    AI audit

    £1,500About two weeks

    We map your systems and data, then pick the one or two automations with the clearest return.

    • Workshop with your team
    • Systems and data review
    • Shortlist with the expected return
    • Costed build plan

  2. Step 2

    Build

    From£3,000Agreed in the audit

    We build the automation into the tools you already use, test it on real examples and roll it out.

    • Integration with your systems
    • Testing on real examples
    • Guardrails and monitoring
    • Team handover

Go ahead with the build and the £1,500 audit fee comes off it.

Book a free call

How it works

Four clear steps.

  1. 1

    Compass

    Audit

    An audit of the tasks worth automating and the data behind them.

  2. 2

    Pillar

    Prototype

    Prove the approach on real examples, fast.

  3. 3

    Forge · Bridge

    Integrate

    Build it into your product, with guardrails.

  4. 4

    Sentinel · Everest

    Evaluate & launch

    Score quality, watch costs, then roll out.

See our full eight-phase process

What you receive

Everything you walk away with.

All yours, documented and ready to use, whether you stay with us or not.

  • Documented
  • Handed over
  • Yours to keep
  1. 01AI audit and costed build plan
  2. 02Data and privacy review
  3. 03Working prototype
  4. 04Quality test set and results
  5. 05Integration into your product
  6. 06Guardrails and fallbacks
  7. 07Usage and cost monitoring
  8. 08Team handover and documentation

What clients say

In their words.

“How detailed and attentive..Trusted and results driven and also the level of patience they have no matter my complaints 😩😁”
Oluwatosin
“Dealt with Naqvi from start to finish and very happy with the service provided. Went through everything in detail when I needed it”
Mr A Lockley
“Great communication and clear project updates from beginning to end. We always knew what stage the app was in.”
Abernathy Verified

Thinking about ai integration & automation?

Tell us what you need and we'll come back with a plan, a timeline and a clear price.

Book a free callEstimate cost

Why Vebryx

Why founders choose us.

Validation first

We test demand first, so every feature is backed by real users.

Clear scope, fair price

Transparent pricing and regular updates. No surprises.

Built to scale

Proven tech like React, Next.js and AWS, ready to grow.

What you get

Hours back

Manual work handled in seconds.

Grounded answers

Responses from your data, with sources.

Costs in view

Usage and spend tracked from day one.

Tech stack

Proven tools, chosen for your product.

  • Anthropic ClaudeModels
  • OpenAIOpenAIModels
  • Google GeminiModels
  • Hugging FaceModels
  • PythonBuild
  • LangChainBuild
  • PyTorchBuild
  • Node.jsBuild
  • Next.jsBuild
  • PostgreSQLData
  • SupabaseData
  • RedisData
  • AWSAWSCloud
  • AzureMicrosoft AzureCloud
  • Google CloudCloud
  • VercelCloud

Industry experience

Sectors we know well.

FAQ

Common questions.

  • Yes. The product, the designs and the code are yours, handed over with the technical documentation.

Compare

Prompting, retrieval or fine-tuning?

Three ways to make a model useful for your business. Many products combine them.

Prompting

Best for
Simple, general tasks
Your data
Not used
Set-up effort
Low
Keeping it current
Edit the prompt
Running cost
Lowest

Retrieval (RAG)

Best for
Answers from your own content
Your data
Looked up at answer time
Set-up effort
Medium
Keeping it current
Update the documents
Running cost
Moderate

Fine-tuning

Best for
A consistent format or tone
Your data
Trained into the model
Set-up effort
High
Keeping it current
Train again
Running cost
Higher to set up

Know before you start

What makes AI work in production.

Demos are easy; dependable AI features are not. This is how we get from one to the other.

  1. 01

    Start with the task, not the model

    Pick one job with a clear outcome, such as drafting a reply or extracting data from invoices. A narrow task is easier to measure, cheaper to run and far more likely to survive contact with real users.

  2. 02

    Ground answers in your own content

    Retrieval means the model looks up your documents before it answers, and cites what it used. It keeps answers current and makes confident-sounding nonsense far less likely than a model answering from memory.

  3. 03

    Measure quality before launch

    We build a test set of real examples and score accuracy, speed and cost against it. That turns "it feels better" into evidence, and shows when a cheaper model would do the same job.

  4. 04

    Plan for cost, privacy and failure

    Usage-based pricing means costs grow with success, so we monitor spend from day one. We agree what data may leave your systems, and design a sensible fallback for when a model is slow or unavailable.

Insights

Related reading.

Ready to start step one?

Book a free 30-minute call and we'll map out your journey together.

Book your free strategy callGet an instant estimate
  • 30 minutes, no obligation
  • Scope and price agreed up front
  • You own everything we build
  • 4.3 on Trustpilot