Annotation Services
A guide to selecting the best annotation services
Developing machine learning (ML) algorithms and artificial intelligence (AI) models requires comprehensive training datasets so that the projects deliver as per requirements. Preparing these datasets involves annotating and labelling massive amounts of raw, unstructured data, which is a tedious and labour-intensive task. It’s a time-consuming exercise to assign your in-house AI developers and data scientists to these tasks; instead, they would be best served by focussing solely on crucial AI and ML facets of the project.
Considering the substantial amount of data it takes to create usable datasets, one can save a great deal of time and effort by engaging the expertise of a data annotation outsourcing services to develop high-quality training data. At the same time, your team can, instead, focus on building a strong AI. Let’s look at some key aspects to consider when selecting a proficient data annotation company.
An experienced and capable workforce
The increasing use of intelligent, automated processes across industries has led to a growing demand for data annotation service providers. This demand has, in turn, led to the emergence of several organisations that promise specialised data annotation services. For your AI and ML projects to perform as intended, the data labelling and annotation process demands a level of precision and accuracy that can only be possible to achieve with a highly experienced and driven team at your disposal.
Detailed annotation involves manually identifying, organising, filtering, and labelling huge amounts of data, and partnering with a relatively inexperienced service provider can lead to less-than-desirable results. This is why it is crucial to work with a reputable organisation with a highly specialised and experienced workforce to ensure high-quality results.
An adaptable ecosystem
Data annotation companies must be able to adapt and up to date with latest developments regarding various AI and ML systems as they change and evolve. When selecting a data annotation and labelling partner, ensure that they have the ability and are willing to constantly adapt to your organisation’s various AI data training requirements without compromising on the quality of data delivery.
Contemporary tools and technology
Modern data annotation and labelling tools significantly streamline the tedious annotation process by minimising human involvement and maximising efficiency without compromising on data quality. A data annotation company that doesn’t employ cutting-edge technology puts you at an immediate disadvantage by wasting valuable time and resources, which delays your project. A competent data annotation service provider will be armed with the latest industry tech to accelerate the annotation process and ensure high-quality datasets.
Robust data security
Outsourcing annotation services involves sharing sensitive business information with a third party, which is bound to raise data security concerns. Inquire about a prospective annotation partner’s security protocols and ensure that they have the latest data protection systems in place. It is also wise to verify if the data annotation company requires their team of annotators to sign confidentiality agreements with you so that you can be assured that sensitive data is in safe, responsible hands.
Open lines of communication
Constant communication and collaboration between the outsourced data annotation team and your in-house AI training specialists keeps your project on schedule. Ensure that your service provider is willing to maintain open communication channels between the two groups to enable quick response times and adherence to targeted timeframes. If a company does not maintain open lines of communication, they are probably not the right annotation partner for you.
Reasonable pricing
You probably have budget limitations in place for various tasks. Therefore, it is important to have a clear idea about the expenses on data annotation before engaging with a data annotation outsourcing services provider. It is wise to pick a service provider that can evaluate your project and review the magnitude of data involved before quoting a price for their services. A proficient vendor will not only provide you with a clear idea of the cost involved with your project but also project ROIs over time to help you make an informed decision.
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How can Infosys BPM help?
With years of experience in this domain, incorporating the latest methodologies to create high-quality datasets, the Infosys BPM suite of annotation services for AI and ML could be what you’re looking for to bring your machine learning algorithms and artificial intelligence models to life. Discover the right data annotation process for you.
