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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.
We build ML models to analyze historical data to make data-driven predictions about future events.
Enterprise can use these machine learning models to sort things into groups based on their characteristics.
With these type of ML models you can get suggestion on things that you might like based on users past behavior.
These kind of ML models help enterprise to get notified for anything unusual. They help detect fraud, identify defects etc.
We can build models like GPT to understand and work with natural human language, just like ChatGPT.
Enabling machines to "see" and recognize things in images or videos. Enterprises leverage computer vision in different ways.
Machine Learning makes data easy to understand. It creates graphs and charts, organizes data points, and helps spot patterns in information.
With machine learning and generative AI, enterprise can automate tasks like sorting, organizing, and generating content.
Using ML techniques, enterprises can find the best possible solutions to complex problems, it helps optimizing operational efficiency.
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.
We have developed 100+ ML models for small to large scale enterprises including some Fortune 500 companies. Take some time out to browse through our top machine learning project references.
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There are many benefits to hiring a machine learning consultant, including:
The process typically involves project scoping, data collection and preparation, model development and training, testing and validation, deployment, and ongoing monitoring and optimization. We work closely with your team at every step.
The timeline varies depending on project complexity and scope. However, we aim for efficient and timely delivery. We can provide more specific estimates during project scoping.
We prioritize model explainability and can employ techniques such as feature importance analysis, SHAP values, and LIME to provide transparency into model decisions.
“They brought in their best to support us.”
Kumar Mankala Advisor of AI/ML Program, SCE