How to choose the best data annotation outsourcing company?
In 2022, “the global artificial intelligence market size was valued at USD 136.55 billion”. According to Grand View Research, it is expected to have “a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030”. To apply AI in many aspects of life, the quality of the input data greatly impacts the actual intelligence and competency of an AI model. Thus, AI companies always look for high-quality data annotation and labeling solutions to train their AI. Many companies only rely on their internal teams; otherwise, many other companies choose to use outsourcing services.
Not to mention the AI companies that deal with sensitive information, using outsourcing services is considered a best-case solution for enterprises, offering a shorter deployment time, experienced staff, and more importantly, it helps to save costs. However, choosing a data annotation outsourcing company to work with is not an easy task. If we cooperate with the wrong vendor, it can lead to poor-quality services, a waste of money, and project delays.
So, how to find the best data annotation outsourcing vendor? Let’s follow us to understand the key factors to consider for an appropriate data annotation vendor.
1. A project requirement
For the vendor to meet the project’s demands, businesses need to define clearly the criteria and requirements of the upcoming project, including accuracy rate, timeline, price, levels of annotator, the type of data which needs annotating, the volume of data, and the type of annotation. The initial clarification is the key to avoiding misunderstanding, back-and-forth questions and unnecessary errors.
At the beginning of every project, it is essential to determine the budget for the data annotation projects. Asking questions about budget from the start will help companies determine the vendor segment based on location, or expertise level.
Besides cost, quality is also an important factor when choosing a data labeling vendor. Remember to learn more about the vendor’s expertise and capacity through their portfolio, the team size, the growth rate, and also clients’ feedback on reputable company review websites. In addition to the company brochure that the vendor provides, these are objective information sources for you to assess prestige companies.
4. Privacy and Security
When you choose to outsource data labeling projects, you will need to give external vendors the right to access your internal data. To ensure data security, it is certainly important to have a Non-Disclosure Agreement (NDA) in advance for any project. Additionally, if the company has an international security certification like GDPR (Europe) or ISO 27001 (Asia), it will be an advantage.
With the same price segment, the more experienced vendors will be an ideal choice. There’s no doubt that one vendor who carried out a variety of projects will have a better capacity to handle problems, ram up their team, as well as understand the types of data, and conduct an effective QA process to meet the customers’ expectations.
Flexibility can be evaluated in many different aspects. In which, a flexible vendor can use a variety of tools according to customer requirements as well as have the readiness to communicate and report daily, weekly, or monthly via diverse platforms (WhatsApp, Skype, Zalo). Additionally, they may have the ability to handle urgent requests flexibly and build teams with different engagement models (project-based, time & material). In some cases, they can involve a dedicated team in the client’s project to deliver the highest work efficiency.
For example, projects may need to be completed in less time and require more annotators than originally planned, which requires the ability to scale up teams rapidly. The vendor needs to recruit and train a high number of annotators, and QA quickly to meet deadlines.
7. A trial
Before signing a formal contract, we can ask the vendor to do a trial that carried out a small-scale implementation of project samples. A pilot project helps the team to assess the quality of annotated data, project duration, performance, and proficiency of annotators. However, not all vendors are willing to provide a pilot for free. Therefore, you need to ask clearly in advance about the cost of the trial version.
With complex and long-term projects, companies can negotiate to do a short-term PoC (Proof of Concept) in advance so that vendors understand the requirements clearly. This makes businesses recognize the suitability and capacity of the vendor. One other point to note is enterprises need to pay the cost of the PoC process.
After establishing these detailed criteria, it is the right time to evaluate the list of vendors through the initial criteria. This checklist is just our suggestion to help businesses have a better vision of how to choose the right labeling service supplier. The good quality of data annotation will be a basis for efficient AI models.
With many years of experience, LTS GDS was honored to be awarded by Good Firms in 2020 as the top BPO Companies in Vietnam. Besides, we achieved the prestigious 2021 Sao Khue Award for excellent Data Annotation Services.
We’ve performed more than 500 projects in diverse industries such as Automobile, Retail, Manufacturing, Construction, and Sports. These data annotation projects were highly satisfied by the clients with up to 98% accuracy rate, which makes us become a reliable partner of many big corporate around the world like US, Germany, Japan, and Korea…
If you want to find out more detailed information, contact us right now!