Personal blog of Yzmir Ramirez

Artificial intelligence is becoming an increasingly common part of how customer service works — a trend that was accelerated in this past year as so many other services went virtual and digital — and today a startup that has built a set of low-code tools to help enterprises integrate more AI into their customer service processes is announcing some funding to fuel its growth.

Cognigy, which provides a low-code conversational AI platform that notably can be used flexibly across a range of applications and geographies — it supports 120 languages; it can be used in external or internal service applications; it can support voice services but also chatbots; it provides real-time assistance for human agents and usage analytics or fully automated responses; it can integrate with standard call center software, and also with RPA packages; and it can be run in the cloud or on-premise — has closed a round of $44 million, funding that it will be using to continue scaling its business internationally.

Insight Partners is leading the Series B investment, with previous backers DN Capital, Global Brain, Nordic Makers, Inventures and Digital Innovation and Growth also participating. The Dusseldorf-based company had previously only raised $11 million and spent the first several years of business bootstrapped.

Cognigy is not disclosing its valuation but it has up to now built up a concentration of customers in areas like transportation, e-commerce and insurance and counts a number of big multinational companies among its customer list, including Lufthansa, Mobily, BioNTech, Vueling Airlines, Bosch and Daimler, with “thousands” of virtual assistants now powered by Cognigy live in the market.

With 25% of Cognigy’s business already coming from the U.S., the plan now is to use some funding to invest in building out its service deeper into the U.S., Asia and across more of Europe, CEO and founder Philipp Heltewig said in an interview.

“Conversational AI” these days appears in many guises: it can be a chatbot you come across on a website when you’re searching for something, or it can be prompts provided to agents or salespeople, information and real-time feedback to help them do their jobs better. Conversational AI can also be a personal assistant on your company’s HR application to help you book time off or deal with any number of other administrative jobs, or a personal assistant that helps you use your phone or set your house alarm.

There are a number of companies in the tech world that have built tools to address these various use cases. Specifically in the area of services aimed at enterprises, some of them, like Gong, are raising huge money right now. What is notable about Cognigy is that it has built a platform that is attempting to address a wide swathe of applications: one platform, many uses, in other words.

Cognigy’s other selling point is that it is playing into the new interest in low- and no-code tools, which in Cognigy’s case makes the integration of AI into a customer assistance process a relatively easy task, something that can be built not just by developers, but data scientists, those working directly on conversation design, and nontechnical business users using the tools themselves.

“The low-code platform helps enterprises adopt what is otherwise complex technology in an easy and flexible way, whether it is a customer or employee contact center,” said Heltewig. As you might expect, there are some direct competitors in the low- and no-code conversational AI space, too, including Ada, Talkie, Snaps and more.

Flexibility seems to be the order of the day for enterprises, and also the companies building tools for them: it means that a company can grow into a larger customer, and that in theory Cognigy will also evolve the platform based on what its customers need. As one example, Heltewig pointed out that a number of its customers are — contrary to the beating drum and march you see every day toward cloud services — running a fair number of applications on-premises, since this appears to be a key way to ensure the security of the customer data that they handle.

“Lufthansa could never run its customer services in the cloud because they handle a lot of sensitive data and they want full ownership of it,” he noted. “We can run cloud services and have a full offering for those who want it, but many large enterprises prefer to run their services on premises.”

Teddie Wardi, an MD at Insight, is joining the board with this round. “We are thrilled to be leading Cognigy’s Series B as the company continues on their ScaleUp journey,” he said in a statement. “Evident by their strong customer retention, Cognigy has created an essential product for global businesses to improve their customer experience in an efficient and effortless manner. With the new funding, Cognigy will be able to expand their leadership position to reach new markets and acquire more customers.”

ServiceNow announced this morning that it has acquired Passage AI, a startup that helps customers build chatbots in multiple languages, something that should come in handy as ServiceNow continues to modernize its digital service platform. The companies did not share terms of the deal.

With Passage AI, ServiceNow gets a bushel of AI talent, which in itself has value, but it also gets AI technology, which should fit in nicely with ServiceNow’s mission. For starters, the company’s chatbot solutions gives ServiceNow an automated way to respond to customer/user inquiries.

Even more interesting for ServiceNow, Passage includes an IT automation component that uses ” a conversational interface to submit tickets, handle queries and take direct action through APIs,” according to the company website. It also gets an HR automation piece, giving the company an intelligent tool it could incorporate across its Now Platform in tools like ServiceNow Virtual Agent and Service Portal, as well as Workspaces in multiple languages.

The multilingual support was an aspect of the deal that appeals to Debu Chatterjee, senior director of AI Engineering at ServiceNow. “Building deep learning, conversational AI capabilities into the Now Platform will enable a work request initiated in German or a customer inquiry initiated in Japanese to be solved by Virtual Agent,” he said in a statement.

Companies are increasingly looking for ways to solve common customer problems using chatbots, while only bringing humans into the loop when the bot can’t answer the query. Passage AI gives ServiceNow much deeper knowledge in this growing area.

Passage AI, which launched in 2016, has raised $10.3 million, according to Crunchbase data. The company website lists a variety of large customers, including Mastercard, Shell, Mercedes-Benz and SoftBank. The acquisition comes less than a week after the company purchased another AI-focused startup, Loom Systems, one that concentrates on automating operations data.

The deal is expected to close this quarter. ServiceNow will be announcing earnings on Wednesday afternoon.

Conversational AI and the use of chatbots have been through multiple cycles of hype and disillusionment in the tech world. You know the story: first you get a launch from the likes of Apple, Facebook, Microsoft, Amazon, Google or any number of other companies, and then you get the many examples of how their services don’t work as intended at the slightest challenge. But time brings improvements and more focused expectations, and today a startup that has been harnessing all those learnings is announcing funding to take to the next level its own approach to conversational AI.

Rasa, which has built an open-source platform for third parties to design and manage their own conversational (text or voice) AI chatbots, is today announcing that it has raised $13 million in a Series A round of funding led by Accel, with participation from Basis Set Ventures, Greg Brockman (co-founder & CTO OpenAI), Daniel Dines (founder & CEO UiPath) and Mitchell Hashimoto (co-founder & CTO Hashicorp).

Rasa was founded in Berlin, but with this round, it will be moving its headquarters to San Francisco, with a plan to hire more people there in sales, marketing and business development; and to continue its tech development with its roadmap including plans to expand the platform to cover images, too.

The company was founded 2.5 years ago, by co-founder/CEO Alex Weidauer’s own admission “when chatbot hype was at its peak.”

Rasa itself was not immune to it, too: “Everyone wanted to automate conversations, and so we set out to build something, too,” he said. “But we quickly realised it was extremely hard to do and that the developer tools were just not there yet.”

Rather than posing an insurmountable roadblock, the shortcomings of chatbots became the problem that Rasa set out to fix.

Alan Nichols, the co-founder who is now the CTO, is an AI PhD, not in natural language as you might expect, but in machine learning.

“What we do is more is address this as a mathematical, machine learning problem rather than one of language,” Weidauer said. Specifically, that means building a model that can be used by any company to tap its own resources to train their bots, in particular with unstructured information, which has been one of the trickier problems to solve in conversational AI.

At a time when many have raised concerns about who might “own” the progress of artificial intelligence, and specifically the data that goes into building these systems, Rasa’s approach is a refreshing one.

Typically, when an organization wants to build an AI chatbot either to interact with customers or to run something in the back end of their business, their developers most commonly opt for third-party cloud APIs that have restrictions on how they can be customized, or they build their own from scratch — but if the organization is not already a large tech company, it will be challenged to have the human or other resources to execute this.

Rasa underscores an emerging trend for a strong third contender. The company has built a stack of tools that it has open-sourced, meaning that anyone can (and thousands of developers do) use it for free, with a paid enterprise version that includes extra tools, including customer support, testing and training tools, and production container deployment. (It’s priced depending on size of organization and usage.)

Importantly, whichever package is used, the tools run on a company’s own training data; and the company can ultimately host their bots wherever they choose, which have been some of the unique selling points for those using Rasa’s platform, when they are less interested in working with organizations that might also be competitors.

Adobe’s new AI assistant for searching on Adobe Stock, which has some 100 million images, was built on Rasa.

“We wanted to give our users an AI assistant that lets them search with natural language commands,” said Brett Butterfield, director of software development at Adobe, in a statement. “We looked at several online services, and, in the end, Rasa was the clear choice because we were able to host our own servers and protect our user’s data privacy. Being able to automate full conversations and the fact it is open source were key elements for us.”

Other customers include Parallon and TalkSpace, Zurich and Allianz, Telekom and UBS.

Open source has become big business in the last several years, and so a startup that’s built an AI platform that has a very direct application in the enterprise built on it presents an obvious attraction for VCs.

“Automation is the next battleground for the enterprise, and while this is a very difficult space to win, especially for unstructured information like text and voice, we are confident Rasa has what it takes given their impressive adoption by developers,” said Andrei Brasoveanu, partner at Accel, in a statement.

“Existing solutions don’t let in-house developer teams control their own automation destiny. Rasa is applying commercial open source software solutions for AI environments similarly to what open source leaders such as Cloudera, Mulesoft, and Hashicorp have done for others.”

 Microsoft introduced the Azure Bot Framework more than two years ago and companies have been building chatbots for a variety of scenarios ever since. Today, the company made generally available the Microsoft Azure Bot Service and Microsoft Cognitive Language Understanding service (known as LUIS). Read More

 Facebook has gone ahead and purchased Charles Jolley’s conversational AI startup Ozlo. Jolley, formerly Head of Platform for Android at Facebook, will not be returning to the company. The Ozlo team is expected to join Facebook to work on natural language processing challenges. Read More