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With LightTag’s innovative team-based label management software, Primer helps customers accelerate delivery of mission-critical NLP applications
One big obstacle our customers face in operationalizing NLP occurs at the starting line – with data labeling. Better labeling means better data on which to train NLP models, and therefore higher model performance and faster deployment of models into production. One hundred great labels can mean the difference between a model changing the business outcome, or it just being another underperforming prototype.
However, customers consistently tell us that labeling documents is a time-consuming, repetitive, and error-prone task and they need better solutions. Building good NLP models that you can trust, especially for the mission-critical customer applications Primer supports, is vitally important.
A key ingredient in our secret sauce has always been meticulous control over the quality of our data and its cost of production. In response to customer demand, I’m thrilled to announce today that Primer has addressed this pain point by acquiring LightTag and that Tal Perry, the founder and CEO of LightTag, is joining Primer as Principal Product Manager.
LightTag’s team-based labeling solution offers innovative features for project management, annotation scoring and conflict management, and quality control. For the last two years, we’ve relied on LightTag’s quality assurance mechanisms to review our labeled data, and our models.
LightTag makes it easy to set up labeling tasks for teams of labelers, accelerating the time it takes to start training NLP models. This can be done online, with labeling commencing in minutes. If you need to train a model on sensitive data, you can deploy LightTag on premises in a secure environment.
LightTag’s UI is geared toward project management, saving tremendous time and effort for those who currently use Excel or Google sheets to manage hundreds of cross-team projects. Instead of cleaning and labeling data sets, data scientists are free to focus on the key problems they need to solve.
Primer gives anyone the power to build and train models more efficiently with autoML strengthened by Data Map and active learning, no coding or technical skills required. Data Map automatically surfaces potential mislabeled data so customers know what to re-label to improve their model’s performance dramatically faster, and active learning identifies the labels that will best improve model performance, reducing the amount of labeled data needed to train a NLP model by up to 30x.
By combining Primer’s machine-driven programmatic labeling capabilities with LightTag’s innovative human-driven labeling, and a full-service white glove labeling solution, we provide an end-to-end labeling solution that serves the full range of customer needs—whether you build your own models using LightTag, customize our models for your use case, upload your pre-labeled data, or let Primer give you a hand with labeling to save you even more time. This combination of human and machine intelligence is essential to achieving the accuracy, trust, and explainability required to rapidly label, build, and deploy NLP models at enterprise scale. With this acquisition, our customers can accelerate knowledge transfer across domain experts by making it easy for them to teach machines what they know thereby decreasing time to value of a wide variety of NLP applications.
Primer is an enthusiastic user of LightTag, having used the product to label hundreds of thousands of documents to train Primer ML models. As part of our acquisition, we’re offering the LightTag capabilities that made us successful to our customers free for anyone up to 5,000 labels per month. Nonprofits and academic users can continue to apply for a free team license on the LightTag website. We will maintain LightTag as a standalone product, so for all the current LightTag customers that know and love the product, you’ll continue to get the same great experience. LightTag by Primer will continue to operate and be available as both a SaaS offering, and an on-premise and air-gapped deployment for customers with high-security requirements.
As of today, users of LightTag can try out Primer Engines to provide predictions and pre-annotations to accelerate their labeling. As a next step, key features from LightTag will be integrated into the Primer NLP Platform, enhancing Primer’s ability to build and scale world-class NLP models that automate and accelerate the analysis of massive unstructured, text-based datasets. With Primer, organizations of all sizes can harness their data to deliver timely and reliable insights to achieve mission objectives and competitive advantage.
I want to take the opportunity to welcome all of LightTag’s customers to Primer. We are excited to continue to support all your NLP use cases and will be doubling down on our investment into LightTag to make it the best NLP labeling software in the world. LightTag bolsters Primer’s strategy to be a world leader in industrial-grade NLP solutions that transform “information overload” into “mission-critical intelligence” for faster human decision making and better outcomes.
As the world continues to change rapidly, Primer stands side by side with our customers to help them address new and emerging challenges and opportunities, from disinformation and cyber/physical security to brand reputation, global customer insights, supply chain impact, and more.
At Primer, we are building the infrastructure to support the creation and deployment of the mission-critical NLP models. LightTag builds out a core part of the Primer infrastructure and complements our Automate and Engines products.
You can access LightTag here — login and get those labels together to train all your NLP models for free!
For more information about Primer and to get a demo, contact Primer here.
Teaching machines what we know, so that they can do things we can’t.