AI & ML Engines
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AI & ML are often used interchangeably without realizing the difference between them. AI is a technology which can stimulate human like intelligence, take decisions and carry out daily tasks that a human can do without supervision. Accelerate business infrastructure and agility with AI expertise, technical services, and machine learning capabilities.

ML is the application of AI into daily tasks, continuously learning by accumulating data, making connections on basis of analysed data and use that to improve the work efficiency without explicitly programmed. Also the algorithms will help in process unutilized or non-utilized data, identifying the trends, which would not be apparent to a human being – and then make decisions to meet specific objectives.

Some insights over AI & ML

84%

Of company representatives believe that investing in AI can bring more competitive advantages.

40%

Of business leaders believe AI will increase worker productivity

80%

Of customer interactions will be handled without a human

40%

Boost can be achieved by Current AI Technology

What we Offer?

Sparrow’s AI & ML services help industries to identify the areas of business that would benefit from these Technologies.

Assist industries throughout the data journey – from navigating Complex data challenges and prototype building – to enterprise-wide AI ML deployment.

Use best practices from requirements gathering to deployment and testing for the solution development life cycle.

Integrate the model with existing or newly developed application and provide support services to make sure it works on a broader and different data set.

Benefits

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Smart Maintenance – Predictive maintenance using complex AI algorithms like ML for all your assets and machinery which will help reduce your downtime and increasing the Remaining useful life of equipment.

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Quality improvement – Help you meet the highest standards and regulations in terms of quality by monitoring defects and sending alerts during problems in production line that can result in quality issues.

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Better product development – Using generative design to get the best out of a product from available production resources, budget and time.

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Rapid analysis and processing – Through the huge data base and use of analytics.

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