By creating a Proof of Concept (PoC) of your AI or ML product you verify the idea on an early stage of development. With the AI & ML engineers engaged in the R&D phase you plan your product development on data not hypotheses. And this ensures the high ROI better decisions in your project.
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The process we’ve developed for taking an AI/ML project from conception to delivery spans 3 full days, broken down into 6 distinct steps.
We call this our Cloud Accelerator Programme - and businesses are generally surprised to discover that it’s completely cost neutral for clients whose digital transformation project will require a $750 monthly spend on the Amazon Web Services (AWS) platform moving forward.
Here, we’ll take a look at what each of those steps entails - as well as the time investment required for each part of the process.
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If you’re reading this, you’re thinking about what artificial intelligence or machine learning could bring to your business. We can transition into your process at any stage, whether you’ve got fleshed-out ideas about how you could use AI/ML, some work done with another provider, or even if you’re just beginning to be aware of a buzz around AI in your industry and want to make sure you’re keeping pace.
However developed your ideas are, we recommend starting with a ‘discovery’ call. This is a chance for us to get to know your product, the technical capabilities you have in-house or through an external service provider, and your vision for how AI or ML can be deployed and scaled.
The process we’ve developed for taking an AI/ML project from conception to delivery spans 3 full days, broken down into 6 distinct steps.
We call this our Cloud Accelerator Programme - and businesses are generally surprised to discover that it’s completely cost neutral for clients whose digital transformation project will require a $750 monthly spend on the Amazon Web Services (AWS) platform moving forward.
Here, we’ll take a look at what each of those steps entails - as well as the time investment required for each part of the process.
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AI and ML solutions are almost certainly going to be working hand-in-hand with intellectual property and sensitive data. As such, it’s never too early to think about best practices around security and recovery.
At this stage, we’ll connect again to discuss your existing security, disaster recovery, and data integrity infrastructure and compare it to the best practices and automation we’ve created to develop and streamline these essential factors.
Of course, managing future billing and cost optimisation in cloud-based AI/ML is also a crucial part of any decision-making process.
Embarking on an AI/ML project isn’t just about having the right tools - it’s about making sure your team is fully equipped to use them.
To ensure this is the case, we’ll design a half-day immersion programme specifically designed for your in-house team. The session will focus on relevant technologies that are part of your AI/ML journey and will blend theoretical understanding with hands-on practice.
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With ideas developed, proven best practices in place and your team’s knowledge honed, we’ll spend a full day creating a tangible, working model of your AI/ML project within your AWS environment.
We’ll work with you to make sure the proof of concept (POC) or minimum viable product (MVP) that’s delivered aligns perfectly with your digital transformation objectives.
This stage also includes forward thinking about efficacy and scalability of your AI/ML solution.
Where prior immersion training was a simulator session, the final step of the process sees your project take flight and focuses on handing over the controls to your team.
To do this, we’ll use AWS’s exceptionally effective “Well Architectured Framework Review” (WAFR). The process looks at key concepts, design principles and structural best practices for running AI/ML workloads in the cloud.
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Step into the future of innovation with our bespoke AI solutions. From preliminary exploration to full-scale implementation, we're committed to your successful AI transformation journey.
Free 6-hr AI exploration workshop: Analyze your business, explore AI applications, get personalized insights & adoption roadmap.
Intensive 2-day workshop that will help you translate concepts into implementable AI solutions with integration plans, data governance, risk mitigation
Our service ensures structured AI validation, managing risks, reducing financial burden, and accelerating ML projects with proof-of-concept and detailed recommendations.
Our implementation practice for machine learning models ensures a smooth transition from prototype to to a fully developed solution ready for production.
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