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Artificial Intelligence Services

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

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Empowering businesses with AI-driven solutions

  • Deep Learning

    Build machine learning solutions on the basis of cognitive algorithms that extract information from big datasets in real-time and classify it in meaningful categories without needing human input.

  • Computer Vision

    Discover and analyze content, accelerate extraction, and deliver highly accessible products that more people can use by embedding vision capabilities into your applications.

  • Enterprise Security

    Ensure endpoint protection over your systems with machine learning algorithms that analyze data to find patterns and detect malware in encrypted traffic, insider threats, and suspicious user behavior.

  • Natural Language Processing

    Gain better insights from unstructured data by interpreting human languages and behavior with speech recognition, natural language understanding, and natural language generation.

  • Predictive Analytics

    Use your historical or existing performance data by implementing predictive models that forecast business results, market trends and user behavior so you can take relevant actions.

  • Process Automation

    Design and implement self-learning processes tailored to automate business process, reduce downtime and obtain end-to-end workflow visibility.

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How can AI be successfully 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:

01

Develop a clear AI strategy that aligns with the organization’s goals.

02

Assemble a team with the right skills and expertise to develop and implement AI solutions.

03

Ensure that the organization's data is reliable, well-structured and of sufficient quality.

04

Choose appropriate AI tools and technologies that align with the organization's needs.

05

Test and refine AI models and solutions before deploying them in production.

06

Ensure that AI solutions comply with relevant regulations, cyber security requirements and ethical concerns.

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About 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 model repository addressing common pain points to quickly deliver value

  • Proprietary AI solution implementation methodology based on previous experience

  • End-to-end capabilities in core areas such as Computer Vision & Natural Language Processing, and Data Science

  • Dedicated cross-functional AI team with skills ranging from hardcore science to product app development

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Unlock AI for your business with Accedia

  • 1

    Business needs definition

    We define your business needs, understand user requirements, the problem domain, and data sources. Our goal is to create a clear problem statement outlining the problem, its scope, and expected outcomes.

  • 2

    Strategic planning

    Our AI consultants review your IT infrastructure, data assets, and business processes to understand strengths, weaknesses, and AI adoption opportunities. We also assess risks and develop an implementation roadmap with clear goals, KPIs, and desired outcomes.

  • 3

    AI model development

    We select the appropriate algorithm, configure the model, and train it with your data. Often, we develop a prototype to demonstrate how the AI solution can address your business challenges or uncover new opportunities.

  • 4

    Model evaluation

    We evaluate the model to ensure it meets performance metrics and accuracy levels. If it does, we deploy it in the production environment and continuously monitor it for compliance and effectiveness.

Our 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.

    • TensorFlow
    • PyTorch
    • Caffe
    • Theano
    • Microsoft Cognitive Toolkit
    • Azure Machine learning
    • Amazon Machine learning
    • Databricks
    • Accord network
    • Scikit learn

FAQs: navigating AI projects and technologies

  • What is your industry experience with AI projects?

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    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.

  • Have you worked with generative AI models and chatbots?

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    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 language can be used?

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    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?

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    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.

Among our 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, optimizing marketing spend and customer interactions. Predictive modeling speeds insights up to 14 times.

  • Sentiment Analysis

    Monitor public opinion and manage the brand’s reputation by analyzing user-generated content from social media. Texts are classified as positive, negative, or neutral, and as more data is collected, the algorithm improves its sentiment assessment.

  • 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.

Get in touch

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