We asked Credible AI Platform to audit our customer-service chatbot. Within three weeks they identified a 22% drop-off in our booking funnel caused by a single misclassified intent. The fix took two days. That one correction recovered roughly £14,000 a month.

— D. Hargreaves, operations lead at a Belfast hospitality group

Team reviewing AI analytics results in a bright office

Artificial Intelligence services priced by what you actually need

Most AI firms sell bundles. You pay for modules you never use, locked into quarterly contracts before anyone has measured what your data can realistically support. We price each component separately, so you build the scope yourself. Below is every service we offer, what it costs, and what determines the final figure.

Component pricing explained

Each row is an independent deliverable. Combine any number of them. Costs scale with data volume and integration complexity, not with arbitrary tiers.

Component	Starting from	What drives the cost up	Typical timeline
Data audit and readiness assessment	£1,200	Number of data sources, whether schemas are documented	5–8 working days
Custom classification model	£3,400	Label count, class imbalance, required accuracy threshold	3–6 weeks
Natural-language processing pipeline	£4,100	Language count, domain-specific terminology, real-time vs batch	4–7 weeks
Predictive analytics dashboard	£2,800	Feature count, refresh frequency, hosting environment	3–5 weeks
Computer vision prototype	£5,500	Image volume, annotation complexity, edge-deployment needs	5–9 weeks
Chatbot / conversational agent	£2,600	Intent count, integrations (CRM, booking, payment), languages	3–6 weeks
Model monitoring and retraining	£600/month	Inference volume, drift-detection frequency, SLA level	Ongoing
AI strategy workshop (half-day)	£900	Participant count, pre-workshop data review scope	1 day + report

All prices exclude VAT. We invoice at milestones, not upfront. If a data audit reveals that AI is the wrong tool for your problem, we say so and charge only for the audit.

Capability map

We work across four domains. Each domain contains the components listed in the pricing table, so you can trace every pound back to a specific deliverable.

Language and text

Sentiment analysis, document classification, entity extraction, summarisation, and multilingual search.

Vision and imagery

Defect detection on production lines, medical-image triage support, retail shelf auditing, and document OCR.

Prediction and forecasting

Demand forecasting, churn prediction, pricing optimisation, and anomaly detection in time-series data.

Conversational AI

Customer-facing chatbots, internal knowledge assistants, voice-enabled agents, and appointment-booking bots.

Pick your route

Not every organisation is at the same stage. Choose the entry point that matches where you are right now.

Exploring

You suspect AI could help but have no internal data team. Start with a half-day strategy workshop (£900). We review your data landscape, identify two or three high-value use cases, and produce a written brief you can act on with us or with anyone else.

Ready to prototype

You have a dataset and a clear question. Skip the workshop and go straight to a data audit (£1,200) followed by a single model build. Most prototypes reach internal demo stage within six weeks.

Scaling an existing model

Your proof-of-concept works but production deployment stalled. We handle containerisation, API design, monitoring, and retraining pipelines so the model runs reliably at volume.

Ongoing optimisation

You already have models in production. Our monitoring service (from £600/month) watches for data drift, retrains on schedule, and alerts your team when accuracy drops below agreed thresholds.

Data centre surrounded by Northern Irish countryside

Built in Northern Ireland, serving the UK and Ireland

Our team works from Wehner-under-Wintheiser. We meet clients in person when geography allows and run everything else over secure video calls. Time-zone alignment with UK and Irish businesses means same-day responses, not overnight waits.

What clients say

They quoted us a data audit at £1,400. Finished in six days. The report was blunt about which of our datasets were usable and which were noise. Saved us from building a model on bad foundations.

— R. Donnelly, fintech product manager, Dublin

Our NLP pipeline handles around 3,000 support tickets a day now. Before Credible AI built it, two staff spent half their mornings routing emails by hand. The system has been live since September 2025 with no unplanned downtime.

— T. McAllister, head of support, a Belfast SaaS company

Is your organisation ready for AI?

Not every business needs a machine-learning model. Sometimes a well-structured spreadsheet, a better CRM workflow, or a simple rule-based script solves the problem faster and cheaper. During our data audit we assess whether AI is genuinely the right tool. If it is not, we tell you and recommend an alternative. You pay only for the audit.

Readiness depends on three things: data quality, a clearly defined question, and someone inside your organisation who will own the output once we hand it over. If any of those are missing, we help you fill the gap before writing a line of model code.

Data science notebook on a laptop screen

Questions we hear often

How do you handle data privacy and GDPR?

All data stays within UK-based infrastructure unless you explicitly request otherwise. We sign a data-processing agreement before any data transfer. Personal data is pseudonymised during model training and deleted within 30 days of project completion unless retention is agreed in writing.

Can I start with one component and add more later?

Yes. Each component is self-contained. A data audit does not commit you to a model build. A chatbot project does not require a strategy workshop. You choose the scope at every stage.

What if the model does not meet the agreed accuracy target?

We define success criteria before work begins. If the model falls short after two retraining cycles, we refund the difference between the quoted price and the cost of work completed. This has happened twice in the past two years, both times due to insufficient training data that the audit flagged as a risk.

Do you build on open-source or proprietary tools?

Primarily open-source: Python, PyTorch, scikit-learn, Hugging Face Transformers, FastAPI. We avoid vendor lock-in. If you later want to bring model maintenance in-house, the codebase is yours and fully documented.

How long does a typical engagement last?

A standalone audit takes about a week. A single model build runs three to seven weeks depending on complexity. Ongoing monitoring is month-to-month with no minimum commitment.

Start a conversation

Tell us what you are trying to solve. We reply within one working day, usually with a rough scope and ballpark cost.