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Services- AI & ML
- AI PoC and AI MVP
AI PoC and
AI MVP
While since the mid-2010s, digital transformation has been a fundamental growth idea for startups and SMBs, firms that have been sluggish to adopt it have been rudely awakened by the rapid advancements in artificial intelligence (AI) and machine learning (ML) technology.
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A Brief
You can validate the concept early in the development process by developing a Proof of Concept (PoC) for your AI or ML product. The R&D phase's AI and ML professionals help you plan your product development based on data rather than guesswork. Also, it guarantees a good return on investment and wiser choices for your project.
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Validate and Scale Your AI Vision: From PoC to MVP Success
Starting with a focused Proof of Concept (PoC) lets you evaluate the viability of your idea in a controlled setting before scaling and validating your AI vision. Before going on to the next stage, a Proof of Concept helps identify potential problems and optimise solutions by concentrating on the main goals.
After validation, the process moves forward with the creation of a Minimum Viable Product (MVP), where your AI solution is improved, scaled up, and ready for wider use.
This procedure guarantees that your AI project will be scalable and useful, producing observable commercial outcomes.
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An Hour-Long Discovery Call To Explore Ideas
When you've come to this, you're probably considering how machine learning and artificial intelligence could benefit your company. We can integrate into your process at any point, regardless of whether you've completed work with another supplier, have had ideas about how you could utilise AI/ML, or are just starting to hear about the buzz around AI in your sector and want to make sure you're keeping up.
Regardless of how developed your ideas are, we advise beginning with a "discovery" call. This is our opportunity to learn more about your product, the technical skills you possess internally or through an outside service provider, and your plans for scaling and implementing AI and ML.
The Roadmap: From Initial Concept to MVP
We've built a 3-day method that consists of 6 separate processes to take an AI/ML project from idea to delivery.
Our program is known as the Cloud Accelerator Program, and companies are usually taken aback to learn that it is entirely free for customers whose digital transformation initiative necessitates a $750 monthly expenditure on the Amazon Web Services (AWS) platform going ahead.
We'll examine the contents of each of those phases as well as the time commitment needed for each step in this section.
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Optimal Approaches - Preserving Your Digital Revolution (2 Hours)
Solutions based on AI and ML will most likely collaborate with sensitive data and intellectual property. Therefore, it's never too early to consider security and recovery best practices.
At this point, we'll get in touch once more to talk about your current disaster recovery, security, and data integrity setup and contrast it with the best practices and automation we've developed to establish and optimise these crucial components.
Naturally, a critical component of any decision-making process in cloud-based AI/ML is handling future invoicing and cost optimisation.
Participation: Matching Information and Technology (4 Hours)
Starting an AI/ML project requires more than simply possessing the appropriate tools; it also requires that your team is prepared to use them.
We'll create a half-day immersion program especially for your internal staff to make sure this is the case. This seminar will combine academic knowledge with practical application, with an emphasis on pertinent technologies that are part of your AI/ML journey.
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POC Shipping: Envisioning Concepts Into Reality (1 Day)
Having developed concepts, implemented tested best practices, and sharpened team expertise, we'll dedicate an entire day to building a physical, functional model of your AI/ML project inside your AWS environment.
We will collaborate with you to ensure that the given minimal viable product (MVP) or proof of concept (POC) completely satisfies your goals for the digital transformation.
This phase also entails planning forward for your AI/ML solution's scalability and efficacy.
Examining a Well-Architectured Foundation (1 Day)
The last part of the process involves letting your project take off and focuses on giving your team control, unlike the previous immersion training, which was a simulator session.
We'll use AWS's incredibly useful "Well Architectured Framework Review" (WAFR) to do this. The procedure examines fundamental ideas, design tenets, and organisational best practices for executing AI/ML workloads on the cloud.
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Services For AI MVPs And PoCs
With the help of our custom AI solutions, venture into the future of innovation. We are dedicated to your successful AI transformation journey, from initial investigation to full-scale implementation.
Seminar for AI Basic Research
Free 6-hour workshop on exploring AI: Examine AI apps, analyse your company, and receive individualised insights and an adoption strategy.
AI Solution Creation Workshop
A two-day intensive session that will assist you in transforming ideas into workable AI solutions that include risk mitigation, data governance, and integration plans.
Demonstrations of concept for AI
Our solution guarantees organised AI validation, risk management, cost savings, and ML project acceleration through thorough recommendations and proof-of-concept.
Implementing AI MVP
Our method of creating machine learning models ensures a smooth transition from initial design to a final product ready for large-scale manufacturing.
AI PoC
In essence, an AI Proof of Concept serves as your idea's 'testing ground.' Here, you assess whether the AI solution satisfies your business goals and is technically possible. Here, the emphasis is on low-cost core functionality validation, which enables you to assess whether the AI can produce the desired results before extending its use.
Learn moreAI MVP
The next step is to develop an AI Minimum Viable Product, which aims to market a functional but simplified version of the AI solution, if the AI Proof of Concept is successful. The AI MVP should only include the most crucial functions and provide end users with real value. This method assists in early real-world feedback collection, which may be applied to improve and hone the solution in later iterations.
Learn moreFrequently Asked Questions?
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