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AI & Data: Build AI That Fits the Way Your Business Works

We help companies turn data into something they can actually use. From defining AI strategy and building custom agents to automating workflows and integrating data systems, the focus is always on real, measurable impact.

AI and Data Service Offerings

Explore the services that help you validate opportunities, reduce risk and define the right path forward.

Agentic Sprint

Turn one high-value AI use case into a working agent prototype, tested on real data and measured against business KPIs before you commit to a full build. In 10 days, you get evidence of what works, what doesn’t, and a clear decision on what comes next.

Multi-Agent Orchestration

Build specialised AI agents that work across your processes, data, and existing systems. From role-specific agents to orchestrated pipelines, they take on complex work, share context, and complete workflows end to end.

Workflow Automation

We help enterprises build operational processes that actually scale. Process discovery, integration platform engineering, document automation, citizen-developer governance, and managed operations. One team from strategy to production.

AI Ops as a Service

Keep production AI reliable, governed, and performing over time. From monitoring and retraining to incident response, compliance, and cost optimisation, we operate the full AI stack and continuously improve it against your business needs.

Data and Integration

We engineer the AI agents that reach production. On an open, code-first framework layer, the same class of stack Klarna, Uber, LinkedIn and MUFG run. Human in the loop by architecture. Delivered iteratively by a small, dedicated pod.

Image showing a Q teammate working on their desktop computer

From Idea to Production in 3 Stages

The right decisions at the right time.

01.

Assess

Decide what to build, and why.

02.

Build

Build, integrate, deploy production AI.

03.

Run

Integrate AI-fluent capability into your organisation.

Why Choose Q?

Large Local AI Models

All AI development and testing is performed within our infrastructure. Our software development process is enhanced by large local AI models that support specification, code generation, testing, and review — enabling our teams to focus on quality, validation, and delivering exceptional products.

AI Academy

To continuously strengthen our capabilities, we run an internal AI Academy. Over 100 Q’s experts have already completed the program, specializing in modern AI agent development, with top performers earning AWS AI certifications.

Private Infrastructure: Nvidia H200 GPU Cluster

We invested in our own AI infrastructure, powered by a dedicated NVIDIA H200 GPU cluster. This allows us to train, fine-tune, and deploy AI models entirely on our own hardware — ensuring speed, independence, and maximum data security.

From ISO to AWS, we got it

Quality & reliability

We pride ourselves on delivering top-tier quality and reliability, backed by our AWS Select Tier partnership and recognition by Clutch as one of the top 15 companies in our field. Our commitment is reinforced through ISO-certified standards in quality, security, and privacy – ensuring our clients receive services that are consistently secure, compliant, and dependable.

Partner with us

Looking to turn your data into real business value with AI?

FAQ

What are AI and data services, and how can they benefit my business?

AI and data services help organisations collect, process, and use data to improve decision-making, automate processes, and uncover insights. This can lead to increased efficiency, reduced costs, and new opportunities for growth through better use of existing data.

How do I know if my company is ready for AI and data solutions?

You don’t need a perfect setup to start. If you have access to data and clear business challenges — such as manual processes, slow decision-making, or untapped insights — you’re ready to begin. The first step is usually building a reliable data foundation and identifying high-impact use cases.

What is the difference between data engineering and AI development?

Data engineering focuses on collecting, organising, and preparing data so it can be used reliably. AI development builds on that foundation by creating models and systems that analyze data, make predictions, or automate decisions. Both are essential for delivering practical, production-ready solutions.