Iristel strengthens ties with WiFi-based text+

text+, with its more than 100 million global and 7 million Canada installs, provides both an install base and set of technical capabilities that Iristel can utilize as it pushes affordability in the wireless market 

TORONTO – February 20, 2020 – Iristel Inc., Canada’s fastest-growing telecom services provider, is pleased to announce strengthened ties with California-based text+, a leading mobile communications service that lets anyone text, talk and share for free or cheaply.

“We support the federal government’s commitment to making wireless service more affordable for Canadians and this investment is another example of Iristel doing our part to offer innovative mobile communications services at fair prices,” says Samer Bishay, Iristel President and CEO.

Iristel and text+ have a long-standing strategic supplier relationship as Iristel provides phone numbers for text+ in Canada. The two companies are now further connected through Iristel’s undisclosed financial investment in text+. Also, now text+ is the engine that powers Iristel’s Sugar Mobile and other OTT “over-the-top” initiatives for the Iristel group of companies.

“text+ has been on a global search for strategic partners that align with our commitment to affordability and innovation in the communications space,” says Scott Lahman, text+ Founder & CEO. “There are very few in the telecom industry who align more closely than Samer and his entire team at Iristel.  We’re thrilled to strengthen an already successful relationship and look forward to building industry leading solutions together.” 

Sugar Mobile in conjunction with text+ now serves hundreds of thousands of monthly users in Canada with OTT talk and text services. This customer base is predominantly people without SIM cards who rely on the service as their primary line. Unfortunately, most do not have cellular coverage as there are no affordable plans for them.

“text+ Canadian users are real people using it right now,” Mr. Bishay says. “But who’s to say we couldn’t extend the service beyond WiFi to cellular networks at a low cost to Canadians?”

Cellular is a natural complement to a WiFi-first service offering in order to ensure that critical communication services are always available as users move out of WiFi zones.

The text+ app has been downloaded more than 100 million times and is available for iOS and Android smartphones and devices. The app gives users an active mobile number, an essential in today’s world for verifications required for so many digital services such as apps, banking, shopping and more.

text+ is headquartered in Los Angeles and Iristel joins leading investors like Upfront Ventures, Raine and Kleiner Perkins Caufield and Byers as text+ backers. The business model for text+ includes advertising, microtransactions including a nominal 2.2 cents per minute outbound calling rate, and various subscription offerings.

About Iristel

Iristel is Canada’s fastest-growing carrier providing innovative communication services, including cybersecurity, that are changing how consumers and businesses communicate. Founded in 1999, Markham-based Iristel operates Canada’s largest facilities-based local voice network extending Coast-to-Coast-to-Coast. It also owns Ice Wireless, an LTE-A carrier with operations in Canada’s northern territories and Quebec. Iristel also owns brands such as Sugar Mobile, an Over-the-Top (OTT) app where phone calls and text messages can be transmitted through data, and TDE, a company that offers sale, rental and repair services of telecommunication equipment in Eastern Quebec and Northern New Brunswick.

text+ Provides Early Support to New Android Smart Reply Feature

ML Kit expands into NLP with Language Identification and Smart Reply

05 April 2019

Posted by Christiaan Prins and Max Gubin

Today we are announcing the release of two new features to ML Kit: Language Identification and Smart Reply.

You might notice that both of these features are different from our existing APIs that were all focused on image/video processing. Our goal with ML Kit is to offer powerful but simple-to-use APIs to leverage the power of ML, independent of the domain. As such, we are excited to expand ML Kit with solutions for Natural Language Processing (NLP)!

NLP is a category of ML that deals with analyzing and generating text, speech, and other kinds of natural language data. We're excited to start out with two APIs: one that helps you identify the language of text, and one that generates reply suggestions in chat applications. Both of these features work fully on-device and are available on the latest version of the ML Kit SDK, on iOS (9.0 and higher) and Android (4.1 and higher).

Generate reply suggestions based on previous messages

A new feature popping up in messaging apps is to provide the user with a selection of suggested responses, either as actions on a notification or inside the app itself. This can really help a user to quickly respond when they are busy or a handy way to initiate a longer message.

With the new Smart Reply API you can now quickly achieve the same in your own apps. The API provides suggestions based on the last 10 messages in a conversation, although it still works if only one previous message is available. It is a stateless API that fully runs on-device, so we don't keep message history in memory nor send it to a server.

We have worked closely with partners like textPlus to ensure Smart Reply is ready for prime time and they have now implemented in-app response suggestions with the latest version of their app (screenshot above).

Adding Smart Reply to your own app is done with a simple function call (using Swift in this example):

let smartReply = NaturalLanguage.naturalLanguage().smartReply()
smartReply.suggestReplies(for: conversation) { result, error in
    guard error == nil, let result = result else {
        return
    }
    if (result.status == .success) {
        for suggestion in result.suggestions {
            print("Suggested reply: \(suggestion.text)")
        }
    }
}

After you initialize a Smart Reply instance, call suggestReplies with a list of recent messages. The callback provides the result which contains a list of suggestions.

For details on how to use the Smart Reply API, check out the documentation.

Tell me more ...

Although as a developer, you can just pick up this new API and easily get it integrated in your app, it may be interesting to reveal a bit on how it works under the hood. At the core of Smart Reply is a machine-learned model that is executed using TensorFlow Lite and has a state-of-the-art modern architecture based on SentencePiece text encoding[1] and Transformer[2].

However, as we realized when we started development of the API, the core suggestion model is not all that's needed to provide a solution that developers can use in their apps. For example, we added a model to detect sensitive topics, so that we avoid making suggestions in response to profanity or in cases of personal tragedy/hardship. Also, we included language identification, to ensure we do not provide suggestions for languages the core model is not trained on. The Smart Reply feature is launching with English support first.

Identify the language of a piece of text

The language of a given text string is a subtle but helpful piece of information. A lot of apps have functionality with a dependency on the language: you can think of features like spell checking, text translation or Smart Reply. Rather than asking a user to specify the language they use, you can use our new Language Identification API.

ML Kit recognizes text in 103 different languages and typically only requires a few words to make an accurate determination. It is fast as well, typically providing a response within 1 to 2 ms across iOS and Android phones.

Similar to the Smart Reply API, you can identify the language with a function call (using Swift in this example):

let languageId = NaturalLanguage.naturalLanguage().languageIdentification()
languageId.identifyLanguage(for: "¿Cómo estás?") { languageCode, error in
  guard error == nil, let languageCode = languageCode else {
    print("Failed to identify language with error: \(error!)")
    return
  }

  print("Identified Language: \(languageCode)")
}

The identifyLanguage functions takes a piece of a text and its callback provides a BCP-47 language code. If no language can be confidently recognized, ML Kit returns a code of und for undetermined. The Language Identification API can also provide a list of possible languages and their confidence values.

For details on how to use the Language Identification API, check out the documentation.

Get started today

We're really excited to expand ML Kit to include Natural Language APIs. Give the two new NLP APIs a spin today and let us know what you think! You can always reach us in our Firebase Talk Google Group.

As ML Kit grows we look forward to adding more APIs and categories that enables you to provide smarter experiences for your users. With that, please keep an eye out for some exciting ML Kit announcements at Google I/O.