Getting Started with AI
Your Path from AI-Curious to AI-Powered
Many businesses know AI could help them, but don't know where to start. We aim to cut through the hype to identify real opportunities, validate what will actually work, and build custom systems that deliver results.
These services focus on developing AI solutions tailored to your business: automating processes, extracting insights from data, improving efficiency, or creating new capabilities. Whether you're exploring possibilities or ready to build, each step is guided by hands-on expertise.
How This Works
Four core services cover the most common needs, but every engagement is tailored to your specific situation. You might start with a broad assessment, jump straight to validating a specific idea, or go directly to building what you need.
Quick Overview:
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AI Opportunity Assessment
For businesses exploring where AI could help
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AI Feasibility Assessment
Quick validation of a specific approach's viability
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AI Proof of Concept (POC)
Proving an approach works at scale before full commitment
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AI Implementation
Building production-ready systems
Everything is customised to your company's size, budget, timeline, and specific challenges.
Service Details
AI Opportunity Assessment
For companies asking: "Where should AI be applied in our business?"
What's involved: 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 implementation. If they're not, we'll tell you what needs to be in place first. Where off-the-shelf tools like Copilot or existing AI services are sufficient, we'll recommend those. Where custom solutions are needed, we'll identify those opportunities.
Deliverables:
Workshop with key stakeholders
Assessment of AI readiness (data quality, infrastructure, 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 if AI isn't suitable yet)
Timeline: Varies based on company size and scope. Can range from a focused 1-2 week assessment to a comprehensive multi-department review.
When to choose this: You're interested in using AI within your business, but don't have a specific use case in mind. You want expert guidance to separate genuine opportunities from hype, and an honest assessment of whether you're ready to proceed.
AI Feasibility Study
For companies asking: "Will this specific approach actually work?"
What's involved: A focused, rapid validation of the most challenging or risky aspect of a potential solution. Rather than building a full prototype, this tackles the core technical question: is this approach viable? This is designed to check the feasibility of an approach in the most efficient manner possible, this can also be useful to help scope out a more detailed project, where there may be a number of unknowns at the outset. The key goal here is to de-risk any potential longer-term investigments with this initial 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 POC would involve
Timeline: Highly variable and dependent on the specific question being answered. Could be as quick as 1-2 weeks for a focused technical validation.
When to choose this: You have a specific idea but want to quickly validate the most uncertain part before committing to building a full POC. This is the agile, low-cost option to test viability.
AI Proof of Concept (POC)
For companies asking: "Will this approach work at scale with our real data?"
What's involved: Building a working prototype using your actual data and real-world conditions. This goes beyond the quick technical validation of a feasibility study to prove the approach works end-to-end in your specific environment.
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: Completely dependent on scope and complexity. Timelines are discussed and agreed based on your specific needs and constraints.
When to choose this: You've validated the core approach (perhaps through a feasibility study) and now need concrete proof that it works at scale in your environment before investing in full production. Or you need to demonstrate value to stakeholders with a working system.
AI Implementation
For companies saying: "Build the solution"
What's involved: Building production-ready AI systems that integrate with existing infrastructure. From data pipelines to model deployment to user interfaces, delivering complete solutions that can be operated and maintained.
Deliverables:
Production-ready AI system
Integration with existing systems and workflows
Documentation and deployment guides
Team training and knowledge transfer
Post-deployment support period
Timeline: Highly variable depending on scope and complexity. Timelines are determined based on your specific requirements and constraints.
When to choose this: You have a clear use case and are ready to build. You might have already done a feasibility study or POC, or you're confident enough to go straight to production.
The Approach
Focus on what works, not what's trendy. Every recommendation is grounded in actual data, infrastructure, and business constraints.
Build, not just advise. Deliverables are working systems and concrete results, not just strategic documents.
Transfer knowledge. Teams are trained to operate and evolve solutions independently.
Who This is For
This works with companies of all sizes, from SMEs to large enterprises, across industries including manufacturing, healthcare, professional services, financial services, and retail.
What matters most:
Real business problems AI can solve
Data available (even if it needs work)
Commitment to implementing solutions
Common Questions
Is this about training teams to use ChatGPT or Copilot? No. These services focus on building custom AI systems for your business. If off-the-shelf tools like Copilot solve your needs, we'll recommend those (especially during an assessment), but we don't provide training on consumer AI tools.
Must it start with an assessment? No. If you already know what to build, start with a feasibility study, POC, or go straight to implementation.
Not sure which service is needed? Book a free consultation call to discuss your situation and get a recommendation on the best starting point.
Can this work with existing systems? Yes. The focus is on integrating AI solutions with existing infrastructure, databases, and workflows.
What happens after implementation? Documentation, training, and a support period are provided. After that, your team can operate the system, or ongoing support can be arranged.