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AI has become an increasingly important tool for businesses with applications ranging from personal assistants to complex data analysis. However, despite its numerous benefits, AI development can be a complex and daunting process that requires specialized knowledge and skills. Fortunately, advancements in technology have made AI development simpler and more accessible. With the help of companies like Accedia, any company can now unlock business opportunities by levaringing AI.
The costs for AI development can vary depending on the scope and complexity of the project. Factors that are considered include the type of AI technology used, the amount of data required for training, the complexity of the algorithms, the size of the development team, and the duration of the project. However, with Accedia, clients can benefit from tested and ready-to-use AI models that reduce costs and development time.
The costs for AI development can vary depending on the scope and complexity of the project. Factors that are considered include the type of AI technology used, the amount of data required for training, the complexity of the algorithms, the size of the development team, and the duration of the project. However, with Accedia, clients can benefit from tested and ready-to-use AI models that reduce costs and development time.
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:
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:
Build 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.
Discover and analyze content, accelerate extraction, and deliver highly accessible products that more people can use by embedding vision capabilities into your applications.
Ensure endpoint protection over your systems with ML algorithms that analyze data to find patterns and detect malware in encrypted traffic, insider threats, and suspicious user behavior.
Gain better insights from unstructured data by interpreting human languages and behavior with speech recognition, natural language understanding, and natural language generation.
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.
Facilitate organic interaction with end-users by answering questions, following a conversation and accomplishing customer service tasks with agents like chatbots and virtual assistants.
Design and implement self-learning processes tailored to your business to automate repetitive tasks, reduce downtime and obtain end-to-end workflow visibility.
Choosing the right technology stack is at the foundation of your project success. Expert in wide spectrum of ML and AI, web and mobile technologies, we help you make the best decision, considering your requirements and business specifics.
Use images of defected bearings to forecast future failures in production
Computer Vision models recognize and classify specific damage in uploaded pictures of malfunctioning bearings
Plan petrol distribution to gas stations 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 petrol products
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
Monitor public opinion on a telеcommunication provider’s services and manage the brand’s reputation.
User-generated content such as comments and reviews from different 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.
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.
To start any type of development project or work, the first step is not to simply assemble a team but to determine what collaboration model will work best for your business case. If you’re torn between outsourcing or getting an in-house team, or extending it with outside help, this whitepaper is for you!
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