Email is the most popular form of business communication on the planet, but managing inboxes becomes more complex every year as the amount of emails grows. On average, professionals have more than 200 emails in their inbox and receive 120 new ones each day, but respond to only 25% of them. Finding the most urgent emails in the sea of messages has gotten harder every year — until now.
We’re excited to introduce a new productivity-boosting feature to the Nylas APIs: Categorizer for email. Categorizer automatically distinguishes between human-to-human (H2H) and machine-to-human (M2H) emails, helping users find and respond to the most important messages first.
Now, not only can you quickly connect to your users’ email inboxes to create contextual email experiences within your CRM or application, but you can also supercharge their inbox productivity within your application.
Inboxes can quickly become unmanageable due to the influx of newsletters, login confirmations, password resets, spam, and more. Major email providers have features to clean up users’ inboxes, but tools aren’t universally exposed, resulting in your users spending valuable time sifting through inboxes and often missing important messages.
With Nylas Categorizer, you can build the same time-saving features that Gmail and other service providers offer in a fraction of the time.
Using advanced machine learning models, Categorizer enables your platform to distinguish between H2H and M2H emails with a single API call. Not only can you easily differentiate between the two, but you can get a filtered view of emails from humans or those sent from machines. With this endpoint, you can bring intelligence to your platform without building and training complex machine learning models in-house.
With Categorizer, you can run emails through sophisticated machine learning algorithms that intelligently apply categorization tags to incoming messages instantly. By making a simple PUT request to the api.nylas.com/neural/categorize endpoint, you can distinguish incoming emails between either “conversation” (H2H) and “feed” (M2H).
Learn more in our docs here.
Regardless of the industry, time is valuable. Time spent sifting through crowded inboxes could be spent much more efficiently on tasks that can’t be automated away. By providing your users with a laser-focused view of their inbox, you can increase user productivity and, consequently, the value of your platform.
Here are just two examples of how Categorizer reduces time spent on inbox housekeeping and, in doing so, enables your users to be more productive:
Intelligence is the Future
Driving user productivity is critical in keeping your customers happy and successful. By removing the unwanted noise in your users’ inboxes, Categorizer brings the intelligence needed to take your platform to the next level. See how you can leverage other intelligence features like Signature Extraction and Clean Conversations.
Speak to a platform specialist now to learn more about Categorizer and the Nylas Neural API.
Attributes generative AI advancements, customer-centric innovations, and expanding ecosystem of partnerships to its revenue growth…
Detect and extract text found within PDFs, TIFFs, and handwritten images with the Nylas Neural API.
Customize your data sync settings with Nylas’ flexible Sync Policy.
Dominic is a Product Marketing Manager at Nylas. In his spare time, he loves to hike and go to the beach with his dog.
Email API
Calendar API
Scheduler
Contacts API
ExtractAI
Google email & calendar integration
Outlook email & calendar integration
IMAP integration
Calendar management
Embedded contextual email
Scheduling automation
Automated outreach
Intelligent data extraction
Ecommerce
Telehealth
Real estate
Financial technology
Educational technology
Expense management
Customer relationship management
Applicant tracking system
Communications platform
Marketplaces
Document management
Docs
SDKs
Tutorials
API status
Changelog
Support
Blog
Events
Guides
Inspiration gallery
Partners
Build vs. buy
Customer stories
Security & Compliance
Why Nylas
Newsroom