Build AI and Machine Learning proof of concept (PoC)

We help businesses showcase the real-world applicability of AI/ML technologies, focusing on a single use case to deliver tangible outcomes for your end users.
Build with Us
AI/ML banner image
Leading AI/ML development company verified by
Top ML company

Our AI/ML PoC development services

Explore the possibilities of AI and machine learning to validate hypotheses, demonstrate business value, and lay the groundwork for future AI initiatives.

Build Generative AI Applications

Leverage our expertise to build and scale your GenAI applications using Amazon SageMaker, AWS's fully managed service for building, training, and deploying machine learning models, to generate text, images, or other content.

Learn more
Make your Business Apps Smart

Integrate purpose-built AI services into your existing business applications using Amazon AI services such as Amazon Transcribe for speech recognition and Amazon Textract for document analysis, to enhance functionalities and provide intelligent insights.

Learn more
Build, Train, and Deploy ML Models

Access fully managed infrastructure, tools, and workflows provided by Amazon SageMaker to build, train, and deploy machine learning models for different use cases, ensuring scalability, reliability, and optimal performance.

Learn more
Predict with ML Capabilities

Empower business analysts across marketing, sales, operations, and finance to generate ML predictions using Amazon Forecast and Amazon Personalize for time series forecasting and generating personalized recommendations.

Learn more

Our case studies

Every solution we build aims to solve real-world problems while adhering to the same programming values. Check out our portfolio section below!

Data lake, warehousing & insights for automotive project

We built a Proof of Concept (PoC) for our client to upload unstructured data into the data lake. Which would then be structured and processed in a warehouse for easy, digestible, and filterable insights—all in real-time.

View case study
afg tech case study image
workplace saudi case study image
Saudi air navigation’s - employee engagement suite

Applify assisted SANS by designing and developing a native Android and iOS mobile app tailored for their on-premise servers, fostering seamless communication among employees.

View case study
Food Marketplace
Digitizing wholesale food distribution for over foods

Our team implemented a web platform for admin and finance, mobile apps for ordering and delivery, and a feature-rich web admin panel, leveraging NodeJs, Flutter, and Angular technologies.

View case study
overfoods case study image

Our fail-fast approach for PoC development using AI/ML

Accelerate the value you get out of your data by leveraging AWS and open-source AI and ML frameworks to build your proof of concept with a fail-fast approach.


Our team begins by thoroughly reviewing your data sets, attributes, use cases, and existing heuristics and patterns. This ensures we have a comprehensive understanding of your requirements, laying the foundation for successful AI and machine learning solutions.

Planning & Design

We work closely with you to determine the appropriate algorithms and data for your specific use case. Our experts design the architecture for model training and evaluation, ensuring scalability, reliability, and optimal performance.

Model Development

Next, we build and train the AI and machine learning models. Our iterative approach allows us to refine and tune the models based on feedback and evolving requirements, ensuring they meet your business objectives effectively.

Testing & Validation

We thoroughly test and validate the models, conducting hyperparameter tuning and evaluating performance and quality against predefined metrics. This ensures that the deployed solution meets your performance criteria and delivers actionable insights.

Reporting & Analytics

Our team enables you to track and analyze the performance of the deployed solution. Further, we conduct knowledge transfer sessions to empower your team with the skills and expertise needed to maintain and optimize the AI solution going forward.

FREE consultation for AI/ML proof of concept (PoC) funding program

We offer a free consultation to help you explore the opportunity of launching your first AWS Machine Learning Proof of Concept (PoC) on AWS.

Understand the potential impact of AWS ML PoC on your business.
Anticipate and plan for AI/ML model deployment workload and costs.
Receive guidance on securing funding for your AWS ML PoC.
Ready to embrace AI/ML innovation with a PoC?

Get in touch with us now to discover how our tailored solutions and funding assistance can accelerate your AI/ML journey.

Let's talk

Frequently asked questions

Explore answers to frequently asked questions about CloudX service. Have a question that's not covered? Reach out to our team for personalized assistance.

What is the typical cost of developing an AI/ML Proof of Concept (PoC)?

The typical cost of developing an AI/ML Proof of Concept (PoC) can vary significantly due to the project's specific requirements and complexities. Costs generally range from $10,000 to $50,000 or more, depending on several factors. These factors include the complexity of the data involved, such as its volume, quality, and preparation needed for analysis, and many others. We suggest you get in touch with our team for a detailed quote.

What are the ongoing costs of deploying a successful AI/ML model?

Transitioning from a Proof of Concept (PoC) to a full-fledged AI/ML solution incurs ongoing costs such as model infrastructure, data pipeline management, and monitoring/retraining. These expenses cover deploying and maintaining the model, managing data flow, and ensuring continuous performance optimization.

How long does a typical AI/ML PoC take to complete?

The duration of a typical AI/ML Proof of Concept (PoC) project can fluctuate based on its complexity and specific requirements. However, a fundamental PoC can often be finalized within a timeframe of 4 to 6 weeks, encompassing distinct phases.

What tools and technologies do you use for AI/ML development?

We use industry-standard tools like TensorFlow, PyTorch, and sci-kit-learn for robust model building, training, and evaluation in AI/ML development.

How do you handle the ethical considerations involved in AI/ML development?

We prioritize responsible AI development by addressing data bias and ensuring fair and unbiased results. We prioritize data privacy, adhering to regulations, and obtaining user consent. Additionally, we promote model fairness, striving for equitable outcomes across demographics to uphold ethical standards in our AI systems.

Let's redefine the digital future of your business together.

Schedule a meeting with our business head today.

Get in Touch