If AI wants to eat software, Ango will be its bread and butter
The most profound movement in the next decade will be the transition from logic-based software to learnıng-based software. Conventional rule-based software development systems are slowly being replaced by AI systems that need a tremendous amount of sophisticated datasets to operate efficiently.
Although there has been progress in unsupervised learning methods in recent years, supervised learning still rules the majority of AI/ML algorithms and requires vast amounts of data annotation. The explosion in data requirements pushed companies to outsource their annotation needs, creating a large space on its own along the process.
Data preparation and labeling have become the main bottleneck in the penetration of AI systems in everyday life, representing over 80% of the time consumed in AI/ML projects. Data now makes more than 10% of all AI investment and the data labeling market alone is expected to reach $17B by 2025.
Ango is yet another managed data annotation and labeling platform — for now
Ango is a data annotation and labeling platform with an annotation management tool and a vertically integrated marketplace with expert annotators. The platform enables annotation for image, text, audio, and 3D sensor data through its end-to-end project management hub and automation to speed up labeling.
Ango receives data from its customers, either in raw format or through integrations with data storage and data lakes, and enables teams to annotate faster and refine any existing labels through its AngoHub platform. The platform integrates into the Client’s AI training and deployment pipelines creating a positive feedback loop that allows auto-labeling and increases platform productivity.
Ango is well-positioned to expand both vertically and horizontally
Crowdsourced data platforms and managed data labeling platforms have been around for a while, receiving more than $1B in investments over the past few years, with unicorns like Scale AI, Hive, and Cloud Factory emerging. These new-gen players differentiate themselves by delivering domain-specific services, with an emphasis on quality control and faster annotations. Their in-house engineering teams continuously research and develop new methodologies to speed up manual annotations and put in a strict labeler recruitment process while also providing superior training and management.
Ango aims to position itself as the fastest training data delivery platform by focusing its resources around AI assistance and excelling in human-computer interface technologies. The vision is to utilize the high-quality talent and cost advantages around MENA and Central Asia providing next-day delivery to its customers and also creating impact in the region by educating and employing thousands of annotators.
Turkey is case in point for a fertile ground for establishing qualified annotator pools due to favorable demographic backdrop: with a rapidly growing & young engineering talent base, 50k+ graduating students per year (#2 in Europe) and a developer base that is growing 16.5% annually (#1 in Europe). Turkey is well positioned to create the largest high quality annotator talent pool globally.
The high quality of talent in Turkey is Ango’s core advantage in becoming a vertically-focused domain-specific data labeling platform with an emphasis on serving customers that are tackling the toughest AI problems in industries such as health care, manufacturing, and logistics.
Urul Brothers have the domain expertise to further specialize
Ango is led by two co-founding brothers, Gokhan and Gokalp, with engineering degrees from top universities in Turkey, and prior startup, product management, and software development experience. Both with deeply technical backgrounds, they complement each other well on all aspects of the business, with Gokhan driving the broader vision, and Gokalp leading the commercial aspects of the business.
We are still at the infancy stages of AI/ML and we’ll see a transformation in our everyday software tools which will all be re-developed with AI/ML at their core. Ango aims to benefit from this transformation, by optimizing for speed and specializing in high value-added verticals that require sophistication.
We believe that at this stage, artificial minds are still babies, learning the world from us humans. We are committed to accelerate AI’s understanding of the world by providing AI teams with the highest quality training data there can be. — Gokhan & Gokalp