SunTec.AI has earned a mention in GoodFirm’s latest research on “Budget Planning for AI and Blockchain Development Services in 2025,” offering insights into investment trends, employee training ambitions, and strategies for selecting reliable development partners.
We are thrilled to announce our recognition among the Top AI Development Companies in the USA 2025 by MobileAppDaily – a trusted platform that connects businesses with reliable outsourcing companies aligning with their technical and strategic goals. After a rigorous evaluation of several data labeling service providers, MobileAppDaily listed some of the most reliable firms based on their:
Remember Walmart’s major announcement in 2019 about deploying autonomous floor scrubbers? These machines were designed to navigate and clean floors without human interference. However, there was a problem—the scrubbers frequently collided with obstacles. The issue stemmed from incomplete and inaccurate image annotations. The AI model wasn’t trained to recognize all types of obstacles in the store, leading to repeated errors and damage. So, what did Walmart do? They addressed this issue by feeding their AI model with comprehensive data comprising of more annotated images of the store environment. This enabled the scrubbers to move effectively.
SunTec.AI is pleased to be recognized by Designrush as one of the top Robotics AI companies in the United States. This prestigious acknowledgment is a testament to our unwavering commitment to delivering exceptional data annotation services that empower AI/ML models with high-quality, precisely labeled, contextually rich datasets.
We are delighted to be ranked as one of the leading companies for data annotation services in California by the renowned B2B review and rating platform Clutch. Getting recognized for our data labeling services by a platform like Clutch, which has verified client reviews for 280K+ global providers, is a big achievement. This accolade is a testament to the hard work and dedication of our talented team, as well as the trust and support we’ve received from our valued clients.
SunTec.AI insights have been featured in a GoodFirms survey focused on the growing importance and impact of digital advertising in today’s market. The survey, titled “Traditional Advertising vs. Modern Advertising,” explores the dynamic shifts in the advertising landscape and provides an in-depth analysis of trends, benefits, and challenges associated with both approaches.
Garbage in, garbage out (GIGO) is a popular concept in computer programming that also applies to machine learning and artificial intelligence models. If your AI/ML model is fed inaccurate or irrelevant training data, the results will be unreliable. To train AI models for better understanding and interpretation of real-world scenarios, it is crucial to provide them with a large amount of high-quality training datasets. Annotating vast datasets requires highly skilled annotators in large numbers. For businesses lacking experienced annotators in-house or facing budget constraints, outsourcing data labeling services can be a strategic move.
SunTec.AI is honored to be recognized as one of the top artificial intelligence companies in the US by GoodFirms, a renowned B2B listing and review platform. This accolade underscores our commitment to providing high-quality data annotation services, enabling businesses to develop and train machine learning models.
Farmers have long relied on their expertise to evaluate yields, detect diseases, and predict natural disasters. However, with advancements in artificial intelligence (AI), they can now leverage technology to do these tasks more efficiently and accurately. By using AI models, farmers can gain valuable insights into the health and productivity of their crops, allowing them to make more informed decisions and optimize their farming practices.
AI is revolutionizing industries, from healthcare to automotive. You can see its applications everywhere. However, these AI models rely on high-quality training data to function optimally. When you train AI and machine learning models with data that has issues, the outcomes will not be reliable. Biased results, inaccurate predictions, and poor performance can plague your AI project and make your AI model inflexible and inefficient.