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Choose the Data Labeling Partner That is Right for You

Few companies have put in place the foundational building blocks needed to unlock AI’s full potential. In particular, access to quality training data still remains one of the biggest barriers to generating value at scale.
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The Old Way vs the New Way

Burgeoning demand for labeled data has driven the growth of a variety of data labeling solutions. From business process outsourcing (BPO) to crowdsourcing and self-service platforms for in-house teams, each way of working comes with its own limitations.

The Old Way

Traditional crowdsourcing platforms optimize for quantity over quality; though clients can affordably access a large distributed third-party workforce for their ML projects, annotators do not often have domain expertise and resulting datasets lack quality control. BPO companies may offer more bespoke solutions, but implementation can be expensive and slow, and this approach is not optimized for scaling or the integration of new tools.

VS

The New Way

The Old Way has recently been displaced by a new breed of data labeling companies who differentiate themselves as “managed data labeling services.” This new way prioritizes innovation in their tech, using AI to optimize the annotation process. While their models are domain-specific and more emphasis is placed on the QA process, labelers are still crowdsourced. These massively distributed workforces come with significant downstream risks: lower quality labels, a slower path to production, and a lack of AI governance and ethics.

VS

THE BEST OF THE OLD AND NEW

A product-first mindset with an ethically sourced, directly-managed expert workforce

Sama is the only data labeling platform that solves for accuracy, efficiency and ethics. We reduce time to quality using automation, advanced analytics, and a highly agile training data methodology.

Tech

Workforce

ETHICS

SECURITY

ACCURACY

AGILITY

Labeling Provider Comparison Chart

There are many considerations when selecting a training data partner. Understanding the pros and cons between these options is critical to the success of your training data strategy.

Old Way

BPO Workforce

New Way

Product-Led

Sama Way

Product + Workforce
tech
Grey Red X

2nd generation tech, but not product-led

Grey Minus

Product-led, 2nd generation tech

Grey Green Check

Product-led, 3rd generation tech with a dedicated ML team building better annotation tools

Workforce
Grey Minus

Crowdsourced, lacking domain expertise

Grey Green Check

Receives general training

Grey Minus

Platform, but distributed workforce that can lack domain expertise

Grey Green Check

Platform with directly managed workforce trained on your specific use case

Ethics
Grey Red X

Ethical supply chain not a priority

Grey Red X

Ethical supply chain not a priority

Grey Green Check

Ethical supply chain with supporting 3 year MIT Study

Grey Green Check

One of the first and only B Corp certified AI companies

Security
Grey Red X

Inability to provide high degree of security for clients

Grey Red X

Client data may be kept; highly dependent on partners to secure workforce

Grey Green Check

No Data Retention

Grey Green Check

GDPR, Anonymization Service, ISO Certification

Accuracy
Grey Red X

Unskilled workforce and lack of feedback loop results in low-quality datasets

Grey Green Check

Can provide simple, low context data quickly

Grey Red X

Unskilled, distributed workforce results in low-quality datasets

Grey Green Check

95-99.5% SLA on CV projects

Grey Green Check

Rigorous QA processes (Human in the Loop)

Agility
Grey Red X

Models and annotators not catered to specific industries

Grey Red X

Painful rip and replace

Grey Minus

Unskilled, distributed workforce results in low-quality datasets

Grey Minus

Specialize in a few select industries

Grey Minus

Flexible delivery

Grey Green Check

Advanced and customizable platform, broad range of target industries

Grey Green Check

Flexible delivery and ability to scale according to your needs

Sama’s openness to evaluate the impact of their programs with the rigor of a randomized control trial was refreshing and shows that they’re a leader in the movement toward ethical practices within the AI industry.

David Atkin, Lead Researcher at MIT

Nairobi1

Companies who are making training data their competitive advantage

We’ve been partnered with over 25% of the Fortune 50 for the past 12 years.

Quality is important to Sama. You really get the sense they are there for more than just the financial transaction. They are a true partner.

Vamsi Madabhushi

Vamsi Madabhushi

Senior Manager of Product Management, Walmart

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