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Clearlead AI Consulting

Getting Started with AI

Many businesses know AI could help them but are not sure where to start.

We help companies new to AI identify which problems are worth solving, test whether an approach is viable, and build something that works.

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Services

Which service is right for you?

These four services cover different starting points, from initial exploration through to production. Click or tap to see what each involves.

Not sure which fits? We can help you decide on a free intro call.

Working with your team to understand business challenges and identify where AI can make a real difference. This includes assessing whether your data, infrastructure, and processes are ready for AI. Where off-the-shelf tools like Copilot are sufficient, we will say so. Where custom solutions are needed, we will identify those opportunities clearly.

Deliverables

  • Structured meetings and working sessions with key stakeholders
  • Assessment of AI readiness across data, infrastructure, and organisational capability
  • Analysis of current operations and potential use cases
  • Recommendations for both off-the-shelf tools and custom AI solutions
  • Ranked list of opportunities with ROI estimates
  • Honest recommendations on priorities, including whether AI is the right solution

Timeline

Varies by company size and scope. Can range from a focused 1-2 week assessment to a comprehensive multi-department review.

When to choose this

You want to use AI but do not have a specific use case yet. You want expert guidance to separate genuine opportunities from hype, and an honest view of whether you are ready to proceed.

A focused, rapid test of the most uncertain part of a potential solution: is this approach viable? Unlike a proof of concept, it does not require real production data or a fully integrated build. Answering the hardest question first keeps costs down and avoids committing significant time and budget to an approach that may not work.

Deliverables

  • Focused analysis of the critical technical challenge
  • Small-scale technical validation using sample data or simplified scenarios
  • Assessment of key risks and blockers
  • Clear go/no-go recommendation
  • If viable: outline of what a full proof of concept would involve

Timeline

Highly variable. Can be as quick as 1-2 weeks for a focused technical validation.

When to choose this

You have a specific idea but want to validate the most uncertain part before committing to a full build. This is the low-cost option to test viability before further investment.

Building a working prototype using your actual data and real-world conditions. Goes beyond a quick technical check to prove the approach works end-to-end in your specific environment. Useful when you need concrete evidence to justify investment or to demonstrate value to stakeholders.

Deliverables

  • Working prototype built with your data
  • Performance evaluation and results analysis
  • Technical validation across realistic scenarios
  • Production implementation roadmap
  • Resource and cost estimates for full deployment

Timeline

Dependent on scope and complexity. Timelines are agreed based on your specific needs and constraints.

When to choose this

You have validated the core approach and now need concrete proof it works at scale before investing in full production. Or you need to demonstrate value with a working system.

Building production-ready AI systems that integrate with existing infrastructure. From data pipelines to model deployment to user interfaces, delivering complete solutions your team can operate and maintain. You might have already done a feasibility study or proof of concept, or be confident enough to go straight to production.

Deliverables

  • Production-ready AI system
  • Integration with existing systems and workflows
  • Full documentation and deployment guides
  • Team training and knowledge transfer
  • Post-deployment support period

Timeline

Highly variable depending on scope and complexity. Determined based on your specific requirements.

When to choose this

You have a clear use case and are ready to build. You may have already validated the approach, or be confident enough to proceed directly.

These are starting points, not a fixed menu. Many engagements combine services or sit between them.

If your situation looks different, get in touch and we will talk through what fits.

Not sure where your business stands with AI?

Our free AI Readiness Assessment gives you an objective score across 6 key dimensions, with personalised results and a practical action plan. No call needed. Takes around 10 minutes, or 3 minutes with the Snapshot version.

Take the full assessment3-minute snapshot

Is this for you?

Who this is for

These services work for companies of all sizes, from SMEs to large enterprises, across industries including manufacturing, healthcare, professional services, financial services, and retail. What matters is whether you have a business problem that AI could help solve.

You do not need an in-house data science team or prior AI experience. You do need data (even if it needs work), a specific problem worth solving, and a genuine intent to act on the outcome.

If you are unsure whether AI is right for your situation, we can often give you an honest view on a free intro call. If it is clearly not the right solution, we will say so, without any obligation or need for a formal assessment.

When something else fits better

If you already have AI work underway or know which technical discipline you need, these services may be a better fit:

FAQ

Common questions

Is this about training my team to use ChatGPT or Copilot?

No. These services focus on building custom AI systems for your business, not training on consumer AI tools. If off-the-shelf tools like Copilot meet your needs, we will recommend those during an assessment.

What is the difference between a Feasibility Study and a Proof of Concept?

A feasibility study is a targeted technical check. You identify the most uncertain part of an idea and test whether it is actually viable, without building a full prototype or needing production data. It is the quickest, cheapest way to find out if an approach is worth pursuing.

A proof of concept goes further. You build a working prototype using your actual data, in conditions close to real-world, and prove the approach works end-to-end in your specific environment.

The two often run in sequence: a feasibility study to check the technical question, then a proof of concept to confirm the approach holds up with real data at scale. This reduces the risk of committing to a full build before the approach is proven.

Does every engagement have to start with an assessment?

No. If you already know what you want to build, you can start with a feasibility study, proof of concept, or go straight to implementation. The assessment is for businesses that do not yet have a clear use case and want structured guidance on where to start. If you already have a proof of concept or live system, Scaling & Proving AI is usually the better fit.

How much does this typically cost?

It varies significantly depending on scope, complexity, and which service you need. An assessment is typically far less expensive than a full build. The best starting point is a free introductory call to understand your situation and provide a realistic indication of cost and scope.

Can this work with our existing systems and data?

Yes. We focus on integration with your existing infrastructure, databases, and workflows. We assess data readiness as part of any engagement and explain what needs to be in place before useful AI work can begin.

What happens after implementation?

Every implementation includes documentation, team training, and a post-deployment support period so your team can operate the system independently. Ongoing support can be arranged after that if needed.

Let's Talk

Ready to get started?

Let's talk about where AI can make a difference for your business.

Book a free intro call