SoftServe: Plug for Responsible and Business-proof AI solutions

KEY FACT: The push for more responsive AI solutions would open up business models that could be replicated and profited from. As the world embraces the transformative potential of AI, SoftServe is at the forefront of developing cutting-edge AI solutions while prioritizing responsible and Business-proof deployment.

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Edited on Corel Paint

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Artificial Intelligence (AI) is growing bigger daily and gradually becoming a significant sector of the world's economy. This has placed a demand for education and professional career paths created in that direction. While some persons are updating their skills to be relevant in an AI-driven world, others are setting up firms with a focus on creating AI solutions and this has become a big business in the recent past.

SoftServe, a technology company specializing in consultancy services and software development, has become a big name in creating AI solutions. In addition to AI, SoftServe builds innovative solutions in Engineering Services, including Cloud & DevOps, Big Data, Machine learning, Internet of Things, etc. Regarding Generative AI solutions creation, SoftServe adopts patterns aimed at providing its clients with a heightened sense of urgency.

In a recent update, SoftServe will be showcasing its expertise in its AI initiatives, the challenges faced, and its future strategy for leveraging its powerful technology during the upcoming AI & Big Data Expo North America. At the Expo, SoftServe will be hosting a keynote presentation titled “Revolutionizing Learning: Unleashing the Power of Generative AI in Education and Beyond”. Speaking for the company, Chuck Ros, the Industry Success Director highlighted a recent AI project that exemplifies SoftServe’s innovative approach. Ros explained:

“Our AI engineers built a prompt evaluation pipeline that seamlessly considers cost, processing time, semantic similarity, and the likelihood of hallucinations. It proved to be an extremely effective architecture that led to improved operational efficiencies for the customer, increased productivity for users in the field, a competitive edge for the software company and for their clients, and—perhaps most importantly—a spark for additional innovation.”

Ros pitched that SoftServe's vision is to create an easy-to-use, language model-enabled interface that would allow field technicians to access service histories, equipment documentation, and maintenance schedules seamlessly, enhancing productivity and operational efficiency.

On AI, Ros highlighted the company's awareness of the key mistakes businesses made when deploying AI solutions, including emphasizing the importance of having a robust data strategy, building adequate data pipelines, and thoroughly testing the models. He emphasized his company's resolve to properly assess the feasibility and business viability of AI solutions. In his words:

“We need to pay at least as much attention to whether it should be built as we do to whether it can be built.”

Ros also explained his company's concerns regarding ethical AI development and the significance of human oversight throughout the entire process. He specifically highlighted their strides in managing dynamic data quality, testing and detecting for bias and inaccuracies, ensuring high standards of data privacy, and ethical use of AI systems all require human oversight.

Again, SoftServe's approach to AI development is such that prioritizes structured engagements that evaluate data and algorithms for suitability, assessment of potential risks, and implementation of governance measures to ensure accountability and data traceability.

SoftServe is particular about building AI solutions with the incorporation of a business model to boost productivity. The company is obsessed with refining AI-assisted software development lifecycles and introducing tools and processes that are sustainable and give business-proof outputs.

Many are taking AI more seriously and beyond providing solutions, it is time for AI to be viewed in the business lens for profitability.

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