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Accelerating Your AI Ambition

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Your Partner in Intelligent, Ethical AI Delivery​

Unlock the Value of AI Wherever You Are on the Journey

At Qubit Advisory, we understand that every organisation is at a different point in their AI journey. Whether you’re just starting out, validating concepts, or scaling enterprise-wide AI solutions, our engagement model is designed to meet you where you are.

We offer a modular, flexible approach that allows you to engage with us at any of the four core stages: Discover, Design, Scale or Optimise, based on your needs, internal capabilities, and AI maturity.

Our Client-Centric Engagement Model

  • Set the vision and assess readiness
  • Test high-value use cases at speed
  • ​Operationalise AI across business
  • Drive maturity, ROI, and resilience
  • Discover & Align

    Set the vision and assess readiness

    ​Timeframe: 2–4 weeks

    We partner with your leadership team to shape a clear AI vision, align it to business goals, and assess current capability, data readiness, and regulatory posture (including CPS 230). This phase builds the foundation for informed decision-making and sustainable outcomes.

    What we deliver:

    • Strategy and alignment workshops

    • AI readiness and capability assessment

    • Priority use case identification

    • CPS 230 compliance mapping and guardrails

    ​Best for:

    Organisations new to AI or revisiting their digital strategy.

  • Design & Pilot

    Test high-value use cases at speed

    Timeframe: 4–8 weeks​

    We co-design targeted solutions, deliver proof-of-value pilots, and lay the groundwork across data, platforms, and people. This is where ideas are tested, value is proven, and delivery confidence is built.

    What we deliver:

    • Use case design and PoV or MVP delivery

    • Data and platform readiness

    • Responsible AI frameworks

    • Change readiness and stakeholder engagement

    Best for:

    Organisations with clear opportunities that want to de-risk before scaling.

  • Scale & Embed

    ​Operationalise AI across business

    Timeframe: 8–16+ weeks​

    We transition validated pilots into production-grade solutions. AI becomes part of business-as-usual, supported by integrated systems, skilled teams, and structured operating models that are built to scale.

    What we deliver:

    • Scalable AI solution design and build

    • Integration with business processes and platforms

    • AI operations, performance monitoring, and retraining

    • Uplift of internal capability or managed support models

    Best for:

    Organisations scaling AI into business-critical environments.

  • Optimise & Evolve

    Drive maturity, ROI, and resilience

    Timeframe: 6 week sprints

    ​With AI in production, we focus on fine-tuning performance, uplifting internal capability, and ensuring continued alignment with business, regulatory, and risk needs. This is about making AI sustainable and future ready.

    What we deliver:

    • Model and pipeline performance reviews

    • MLOps uplift, automation, and monitoring

    • Data drift detection and model retraining

    • CoE setup or optimisation and capability uplift

    Best for:

    Organisations with live AI looking to mature capability, improve ROI, and stay compliant.

At Qubit Advisory we can provide a flexible blend of onshore and offshore consultants to help accelerate your AI journey

Planning & Leadership
AI Consultant

Helps you figure out where AI can deliver value. Creates plans and guides your business through your AI journey. 

AI/ML Product Manager 

Coordinates teams to deliver AI tools that work. Sets goals, defines features and ensures your AI projects stay on track. 

AI Architect 

Designs how your AI system will work within your company’s existing tools and data setup. Makes sure it’s secure, reliable and efficient. 

AI Ethics Specialist 

Checks that your AI is fair, transparent and follows ethical and legal rules. Helps avoid bias and builds trust in your systems.

Build & Implementation
Machine Learning Engineer 

Creates and trains AI models, then puts them into use. Focuses on making systems that are reliable and ready to scale. 

Data Scientist 

Finds patterns in your data using statistics and AI. Helps you make better business decisions using insights from data. 

Data Engineer 

Builds the systems that move and organise your data so it’s ready for analysis and AI use. 

NLP Engineer 

Develops AI that understands human language, like in chatbots, search engines or document summaries. 

Prompt Engineer 

Improves how large language models like ChatGPT respond by writing and testing better prompts and instructions. 

Computer Vision Engineer 

Creates AI that understands images and video. Used for things like face recognition, object tracking and safety monitoring. 

AI Research Scientist 

Tests out new AI ideas and helps build early versions of advanced tools. Good for businesses exploring cutting-edge tech. 

AI Software Engineer 

Builds apps and platforms that use AI. Connects the models to the rest of your systems and makes sure everything works smoothly. 

Operations & Support
AIOps Engineer 

Uses AI to help your IT team run more smoothly by spotting issues early, fixing them faster and reducing system downtime. 

AI User Adoption Specialist 

Helps your team learn and use AI tools properly. Provides training, support and change management to encourage adoption.