Practical artificial intelligence for your business

We build machine learning models, automate repetitive workflows, and turn raw data into decisions you can act on. Based in Birmingham, working with companies across the UK.

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Who we are

A small, focused AI consultancy that ships working systems instead of slide decks.

Our AI team collaborating on a project

Credible AI Force started in 2021 when our founders noticed a gap: most AI vendors sold expensive platforms that required six months of integration before anyone saw a result. We took a different approach. Every engagement begins with a two-week discovery sprint that identifies exactly where machine learning will save time or money. If the numbers don't add up, we say so.

Our team includes applied mathematicians, software engineers with production ML experience, and domain consultants who have worked in logistics, retail, healthcare, and finance. We keep the team lean so that the people who scope your project are the same people who write the code.

Birmingham is our home. We chose it because the city sits at the centre of the UK's transport network, and its mix of manufacturing, services, and public-sector organisations gives us a wide range of problems to solve.

120+
Models deployed
38
Clients served
97%
On-time delivery

What we do

Six core service areas, each delivered as a fixed-scope project with clear milestones.

Machine learning development

We design, train, and validate supervised and unsupervised models for classification, regression, and clustering tasks. Each model ships with a monitoring dashboard and retraining pipeline so accuracy doesn't decay over time.

Natural language processing

From customer support ticket routing to contract clause extraction, we build NLP pipelines that parse, classify, and summarise text in English and other European languages. Typical turnaround is four to six weeks from kick-off to production.

Computer vision

Quality inspection on production lines, shelf-stock monitoring in retail, and document digitisation are three of our most requested vision projects. We work with standard RGB cameras whenever possible to keep hardware costs low.

Data strategy and architecture

Before any model can work, the data pipeline has to be reliable. We audit your existing data stores, design ETL workflows, and set up warehouses on AWS, Azure, or GCP depending on your existing stack.

Process automation

We connect AI models to your existing software through APIs and RPA bots. Invoice processing, lead scoring, inventory replenishment alerts: if a human currently copies data between two screens, we can probably automate it.

AI training and workshops

Half-day and full-day workshops for product teams, executives, and developers. We cover prompt engineering, model evaluation metrics, responsible AI practices, and hands-on coding labs with Python and popular ML frameworks.

How we work

Four phases, transparent pricing, and a working prototype before you commit to a full build.

1

Discovery

We interview stakeholders, review your data, and identify the highest-value use case. This takes two weeks.

2

Prototype

A working proof of concept with real data, tested against agreed accuracy thresholds. Usually three to four weeks.

3

Production

We harden the model, build the API layer, write tests, and deploy to your cloud environment with CI/CD pipelines.

4

Support

Monthly model health reports, retraining runs when data drift is detected, and priority Slack or email support.

What clients say

Real feedback from organisations we have worked with over the past three years.

★★★★★
"They built a demand-forecasting model for our warehouse in Solihull that reduced overstock by 22% in the first quarter. The team was honest about what the model could and couldn't predict."
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Rachel Simmons
Operations director, Midlands Logistics Ltd
★★★★★
"We needed an NLP pipeline to classify 4,000 support tickets a day. Credible AI Force delivered it in five weeks, and the accuracy after six months is still above 94%."
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James Okoro
CTO, Finwell Solutions
★★★★☆
"Their workshop on responsible AI gave our product team a clear framework for bias testing. We now run fairness audits on every model before release."
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Priya Kapoor
Head of data, HealthBridge UK

Frequently asked questions

Straight answers to the things prospective clients ask most often.

Discovery sprints start at £4,500. A full prototype-to-production engagement for a single model usually falls between £18,000 and £45,000 depending on data complexity and integration requirements. We provide a fixed quote after the discovery phase so there are no surprises.
Not necessarily. We can work inside your cloud environment under your security policies, or we can use anonymised and synthetic datasets during development. We sign NDAs and data-processing agreements before any data changes hands.
Logistics and supply chain, retail, financial services, healthcare administration, and local government. If your sector is outside that list, the underlying ML techniques still apply; we just pair them with a domain consultant who knows your field.
The discovery sprint takes two weeks. A working prototype is usually ready within five to six weeks from project start. Production deployment adds another three to four weeks. So most clients have a live model inside three months of the first call.
Yes. We deploy on AWS, Azure, and GCP, and we integrate with common tools like Snowflake, Databricks, Salesforce, SAP, and custom REST APIs. If you run on-premise servers, we can containerise models with Docker and Kubernetes for your infrastructure.

Get in touch

Tell us about your project and we will reply within one business day.

47 Colmore Row, Birmingham, B1 1TF, West Midlands, United Kingdom

Monday to Friday, 9:00 am – 5:30 pm