How long does an AI implementation take?

Most single workflow implementations take 2-6 weeks from kickoff to production. Full AI transformation programmes run 6-12 weeks.

Do you work with specific AI models?

We are model-agnostic and work with all major providers including Anthropic Claude, OpenAI GPT, Google Gemini, Meta Llama, Mistral, and more.

Can you deploy AI on our own servers?

Yes. Our Local & Private AI service deploys models on your own infrastructure or private cloud.

comparison

Should I choose custom or off-the-shelf AI?

Quick Answer

Choose off-the-shelf AI when proven products exist for your use case, speed to deployment matters, and standard functionality meets your needs. Choose custom AI when your requirements are unique, competitive differentiation depends on AI capability, or integration needs exceed what standard products support. Off-the-shelf gets you running in weeks; custom AI takes months but fits your exact requirements.

Summary

Key takeaways

Off-the-shelf delivers faster time to value with lower initial investment
Custom AI provides exact fit, deep integration, and competitive differentiation
Off-the-shelf suits standard use cases; custom suits unique requirements
Consider hybrid approaches that customise off-the-shelf foundations

Off-the-Shelf AI: Strengths and Limitations

Off-the-shelf AI products offer proven functionality, faster deployment, and lower initial costs. They benefit from the vendor's development across many customers, providing battle-tested features and regular updates. Popular examples include customer service chatbot platforms, document processing tools, and CRM AI features. Deployment typically takes weeks rather than months, and the vendor handles model updates, security patches, and infrastructure management. However, off-the-shelf products may not perfectly match your workflows, may lack integration with your specific systems, and limit your ability to differentiate. You are dependent on the vendor's roadmap for new features and improvements. Subscription costs can become significant at scale. Data may need to be shared with the vendor for processing.

Custom AI: Strengths and Limitations

Custom AI solutions are built specifically for your requirements, processes, and data. They integrate deeply with your existing systems, handle your specific edge cases, and can provide competitive advantage through unique capability. You maintain full control over the technology, data, and evolution of the system. Custom development is appropriate when your process is unique, your data is proprietary and valuable, integration requirements are complex, or AI capability is a core differentiator. The trade-offs are higher initial cost, typically £50,000 to £300,000+, longer time to deployment, and ongoing responsibility for maintenance, updates, and model management. You need access to AI development expertise, either internally or through a consultancy.

Frequently asked questions

Many products offer customisation through configuration, plugins, or APIs. This provides a middle ground between fully custom and completely standard. Check the extent of customisation available before deciding to build from scratch.

Off-the-shelf: £12,000 to £60,000 per year in subscriptions. Custom: £50,000 to £300,000 initial build plus £10,000 to £50,000 per year in maintenance. Custom becomes more cost-effective at scale or when subscription costs grow with usage.

Trial the product with your actual data and workflows. If it meets 80%+ of your requirements, the remaining gaps may be manageable through workarounds or customisation. If core requirements are unmet, custom development is necessary.

Request a trial period with your actual data and workflows, not just the vendor's demo. Define minimum acceptable criteria before the trial. Involve end users in the evaluation. If the product meets 80%+ of requirements, gaps may be manageable through customisation or workarounds.

Excessive customisation can make upgrades difficult, void vendor support, and create maintenance burden similar to custom development. If you need more than 30-40% customisation, evaluate whether custom development would be more sustainable long term.

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Should I choose custom or off-the-shelf AI?

Quick Answer

Key takeaways

Off-the-Shelf AI: Strengths and Limitations

Custom AI: Strengths and Limitations

Related questions

Frequently asked questions

AI Vendor Evaluation

Custom AI Development

AI Platform Comparison

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