ThirdEye Data offers bespoke machine learning consulting services for enabling enterprises to take data-driven decisions. We develop tailored ML models for specific business needs by using supervised learning, unsupervised learning, time series analysis, reinforcement learning, recommendation systems, computer vision, and NLP techniques.
Enterprises leverage machine learning (ML) models to address a wide range of tasks and challenges across various domains. As a leading ML consulting company, we have hands-on experience in developing cutting-edge ML models to achieve specific business goals.
Manufacturing industry is leading from the front in terms of AI adoption. According to reports, the global AI in manufacturing market size is expected to grow from USD 3.8 billion in 2022 to USD 68.36 billion by 2032, growing at a CAGR of 33.5% over the forecast period 2023-2032.
We have developed & delivered several ML models for manufacturing industry to increase production efficiency, improve product quality, reduce manufacturing costs, and improve on-floor safety measurements. Some of the major applications include:
Retail industry is becoming a leading AI adopter specially to enhance their customer experience and optimize adverting campaigns. Addition to the list, there are some use cases where we have been asked to develop AI-powered cybersecurity applications to protect customer data.
We have developed the following ML models for the Retail Industry:
We can understand the pace of AI adoption in the healthcare industry by one simple statistics. According to a report about 70% of healthcare organizations are currently using AI in some capacity.
We have developed various machine learning models for healthcare industry to improve the quality of care and patient safety. Here some examples:
We have been building various ML models for the EOG industry to increase operational efficiency, reduce risks, and improve operational safety. The models include the followings:
The market for AI in the EOG industry is growing rapidly. According to a report by Grand View Research, the market is expected to reach $11.3 billion by 2028. The growth of the market is being driven by the increasing demand for oil and gas, the need to improve operational efficiency, and the need to reduce costs.
We develop machine learning models for the AdTech industry to analyze in-market audience, building personalized campaigns, forecast demand, create marketing content and boost sales. Our ML models are helping AdTech enterprises to take data-driven marketing decisions. Here are ML models we have built for this industry:
IT industry has always been a fan of data and our ML models are helping them to nurture the data in an enhanced, optimized and secured way. We have built the following machine learning models for the IT industry to improve the data culture:
The market for AI and ML in the BFSI industry is growing rapidly. The growth of the market is being driven by the increasing demand for fraud detection, risk management, and customer service. We have developed the following ML models to serve the need of BFSI industry:
Transportation & Logistics industry is leveraging AI for improving operational efficiency and reduce costs. We have developed the following ML models to serve the industry needs:
The market for AI in the transportation and logistics industry is growing rapidly. According to a report by MarketsandMarkets, the market is expected to reach $32.8 billion by 2025. The growth of the market is being driven by the increasing demand for efficiency, cost savings, and compliance.
According to a recent report, only 30% machine learning projects are successful. There are many reasons why most ML models fail, but some of the common reasons are lack of good data, wrong model selection, overfitting or under-fitting training sessions, scalability, reliability, and security issues.
This is where our machine learning consultants play a vital role. By providing ML expertise, methodologies, and a deep understanding of the business domain, our ML consultants help businesses to overcome the challenges of ML and achieve their business goals.