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AI Development

Looking to take your business to the next level with the power of AI? Learn how AI can be successfully integrated in your project and explore Accedia AI development services to solve problems in innovative and efficient ways!

AI Development made simple

As you are progressing into your AI implementation journey, you may have discovered unforeseen challenges like depth of scientific or programmatic experience required, lack of capacity for development or project management, scarce linkages between engineering and business stakeholders, etc. At Accedia, we leverage our extensive experience in IT consulting services, particularly in the areas of data science, predictive analytics, software engineering, and remote delivery, to provide a tailored approach to AI implementation. Our full-spectrum AI development services provide you with the experience of software engineers, business analysts and data scientists so you can start leveraging the benefits of AI quicker and at a fraction of the cost of developing AI solutions with the existing capabilities of your own team.

  • What is your industry experience with AI projects? What is your industry experience with AI projects?
    What is your industry experience with AI projects?
  • Have you worked with Generative AI models and chatbots? Have you worked with Generative AI models and chatbots?
    Have you worked with Generative AI models and chatbots?
  • What AI development languages can be used? What AI development languages can be used?
    What AI development languages can be used?
  • How to build the right AI team for your needs? How to build the right AI team for your needs?
    How to build the right AI team for your needs?
What is your industry experience with AI projects? Have you worked with Generative AI models and chatbots? What AI development languages can be used? How to build the right AI team for your needs?

What is your industry experience with AI projects?

Our experience encompasses AI development services for industries such as Finance, Energy, Manufacturing, Media & Entertainment and Technology but the advantages of AI can be applied to practically every business domain. Some of the most common use cases include predictive AI capabilities for marketing and customer service, medical image analysis in healthcare, assessing credit risks or performing churn analysis in banking, and optimizing supply chains in manufacturing etc. 

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Have you worked with Generative AI models and chatbots?

Lots of innovation-driven businesses are looking to elevate their customer service to a new level with AI-powered virtual assistants. From using chatbots to communicate and solve customer issues in their digital platforms to building AI models from scratch or tailoring the models behind generative tools such as ChatGPT to address a particular user case, our clients entrust us with their AI development needs. Our experience with generative AI helps businesses increase operational efficiency, bring cost savings or gain competitive advantage.

What AI development languages can be used?

Some of the most popular AI development languages are Python, known for its readability qualities and large number of supportive libraries and frameworks, and R, specifically used for statistical analysis and data visualization. Some more conventional programming languages like Java and C++ are also used for developing AI applications. The most suitable choice for your business depends on your existing technology ecosystem, future scalability needs, skills of the team etc. and is a matter of discussion with your development partner.

How to build the right AI team for your needs?

AI development requires a range of specialists with complementary skills, including data scientists, ML and software engineers, etc. Key skills also include programming, statistics, machine learning frameworks, big data, and distributed systems. The exact composition of the team will depend on the specific goals of your project and the resources available. It's important to identify the necessary roles and skills early on and to build a diverse team with complementary expertise.

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What is your industry experience with AI projects?

Our experience encompasses AI development services for industries such as Finance, Energy, Manufacturing, Media & Entertainment and Technology but the advantages of AI can be applied to practically every business domain. Some of the most common use cases include predictive AI capabilities for marketing and customer service, medical image analysis in healthcare, assessing credit risks or performing churn analysis in banking, and optimizing supply chains in manufacturing etc. 

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Have you worked with Generative AI models and chatbots?

Lots of innovation-driven businesses are looking to elevate their customer service to a new level with AI-powered virtual assistants. From using chatbots to communicate and solve customer issues in their digital platforms to building AI models from scratch or tailoring the models behind generative tools such as ChatGPT to address a particular user case, our clients entrust us with their AI development needs. Our experience with generative AI helps businesses increase operational efficiency, bring cost savings or gain competitive advantage.

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What AI development languages can be used?

Some of the most popular AI development languages are Python, known for its readability qualities and large number of supportive libraries and frameworks, and R, specifically used for statistical analysis and data visualization. Some more conventional programming languages like Java and C++ are also used for developing AI applications. The most suitable choice for your business depends on your existing technology ecosystem, future scalability needs, skills of the team etc. and is a matter of discussion with your development partner.

$item_title

How to build the right AI team for your needs?

AI development requires a range of specialists with complementary skills, including data scientists, ML and software engineers, etc. Key skills also include programming, statistics, machine learning frameworks, big data, and distributed systems. The exact composition of the team will depend on the specific goals of your project and the resources available. It's important to identify the necessary roles and skills early on and to build a diverse team with complementary expertise.

HOW CAN AI BE SUCCESSFULY ADOPTED?

Adopting AI successfully requires careful planning, execution, and management to ensure that the technology aligns with business goals, delivers measurable value, and is deployed ethically and responsibly.  To successfully adopt AI, you should follow these steps:

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accedia AI Capability Center

Accedia’s AI Capability Center is an innovation-driven initiative that aims to make AI accessible to business organizations of all scales. We combine in-depth scientific expertise and end-to-end application development experience to help you make the most of intelligent solutions. You can take advantage of: 

AI technology capabilities

Choosing the right technology stack is at the foundation of your project success. Expert in wide spectrum of  Machine Learning and AI, web and mobile technologies, we help you make the best decision, considering your AI development requirements and business specifics.

AI projects

Predictive Analytics

Use images of defected items to forecast future failures in production.

Computer Vision models recognize and classify specific damage in uploaded pictures of malfunctioning items.

Demand forecasting

Plan network distribution and ensure stability of product supply.

AI is used to develop trained regression predictive models based on ensembles of neural networks, collecting information on the dynamics in consumption of products.

data driven marketing

Deliver insights on subscribers’ responsiveness to promotional campaigns, in view of optimizing marketing spend and improving customer interactions.

Predictive modelling enables the client to get deeper insights up to 14 times faster.

sentiment analysis

Monitor public opinion and  manage the brand’s reputation.

User-generated content from social media networks is the input to a dataset that contains texts classified as positive, negative, or neutral. As data is accrued, the algorithm becomes more confident in assessing sentiment.

Propaganda detection

Overcome the limitations of propaganda classification in the media industry.

A state-of-the-art NLP model for propaganda persuasion techniques analysis was trained to quantify authentic behavior in coordinated groups in social media.

Our competences

Let's talk Artificial intelligence

Connect with us today to discuss your development needs and to get ahead of competitors with the help of artificial intelligence! Here’s how we can start a conversation:

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