INSUBCONTINENT EXCLUSIVE:
For customer service, Ultimate.ai‘s thesis is it not humans or AI but humans and AI
The Helsinki- and Berlin-based startup has built an AI-powered suggestion engine that, once trained on clients& data-sets, is able to
provide real-time help to (human) staff dealing with customer queries via chat, email and social channels
So the AI layer is intended to make the humans behind the screenssmarter and faster at responding to customer needs — as well as freeing
them up from handling basic queries to focus on more complex issues.AI-fuelled chatbots have fast become a very crowded market, with
hundreds of so called ‘conversational AI& startups all vying to serve the customer service cause.Ultimate.ai stands out by merit of having
focused on non-English language markets, says co-founder and CEO Reetu Kainulainen
This is a consequence of the business being founded in Finland, whose language belongs to a cluster of Eastern and Northern Eurasian
languages that are plenty removed from English in sound and grammatical character.&[We] started with one of the toughest languages in the
world,& he tells TechCrunch
&With no available NLP [natural language processing] able to tackle Finnish, we had to build everything in house
To solve the problem, we leveraged state-of-the-art deep neural network technologies.&Today, our proprietary deep learning algorithms enable
us to learn the structure of any language by training on our clients& customer service data
Core within this is our use of transfer learning, which we use to transfer knowledge between languages and customers, to provide a
We grow more accurate the more clients we have and the more agents use our platform.&Ultimate.ai was founded in November 2016 and launched
its first product in summer 2017
It now has more than25 enterprise clients, including the likes of Zalando, Telia and Finnair
It also toutspartnerships with tech giants including SAP, Microsoft, Salesforce and Genesys — integrating with their Contact Center
solutions.&We partner with these players both technically (on client deployments) and commercially (via co-selling)
We also list our solution on their Marketplaces,& he notes.Up to taking in its first seed round now it had raised an angel round of €230k
in March 2017, as well as relying on revenue generated by the product as soon as it launched.The $1.3M seed round isco-led by Holtzbrinck
Ventures and Maki.vc.Kainulainen says one of the &key strengths& of Ultimate.ai approach to AI for text-based customer service touch-points
is rapid set-up when it comes to ingesting a client historical customer logs to train the suggestion system.&Our proprietary clustering
algorithms automatically cluster ourcustomer historical data (chat, email, knowledge base) to train our neural network
We can go from millions of lines of unstructured data into a trained deep neural network within a day,& he says.&Alongside this, our
state-of-the-art transfer learning algorithms can seed the AI with very limited data — we have deployed Contact Center automation for
enterprise clients with as little as 500 lines of historical conversation.&Ultimate.ai proprietary NLP achieves &state-of-the-art accuracy
at 98.6%&, he claims.It can also make use of what he dubs &semi-supervised learning& to further boost accuracy over time as agents use the
tool.&Finally, we leverage transfer learning to apply a single algorithmic model across all clients, scaling our learnings from
client-to-client and constantly improving our solution,& he adds.On the competitive front, it going up against the likes of IBM Watson AI
However Kainulainen argues that IBM manual tools — which he argues &require large onboarding projects and are limited in languages with no
self-learning capabilities& — make that sort of manual approach to chatbot building &unsustainable in the long-term&.He also contends that
many rivals are saddled with &lengthy set-up and heavy maintenance requirements& which makes them &extortionately expensive&.A closer
competitor (in terms of approach) which he namechecks is TC Disrupt battlefield alumDigital Genius
But again they&ve got English language origins — so he flags that as a differentiating factor vs the proprietary NLP at the core of
Ultimate.ai product (which he claims can handle any language).&It is very difficult to scale out of English to other languages,& he argues
&It also uneconomical to rebuild your architecture to serve multi-language scenarios
Out of necessity, we have been language-agnostic since day one.&&Our technology and team is tailored to the customer service problem;
generic conversational AI tools cannot compete,& he adds
&Within this, we are a full package for enterprises
We provide a complete AI platform, from automation to augmentation, as well as omnichannel capabilities across Chat, Email and Social
Languages are also a key technical strength, enabling our clients to serve their customers wherever they may be.&The multi-language
architecture is not the only claimed differentiator, either.Kainulainen points to the team mission as another key factor on that front,
saying: &We want to transform howpeoplework in customer service
It not about building a simple FAQ bot, it about deeply understanding how the division and the people work and building tools to empower
For us, it not Superagent vs
Botman, it Superagent + Botman.&So it not trying to suggest that AI should replace your entire customers service team but rather enhance
your in house humans.Asked what the AI can&t do well, he says this boils down to interactions that are transactional vs relational — with
the former category meshing well with automation, but the latter (aka interactionsthat require emotional engagement and/or complex thought)
definitely not something to attempt to automate away.&Transactional cases are mechanical and AI is good at mechanical
The customer knows what they want (a specific query or action) and so can frame their request clearly
It a simple, in-and-out case
Full automation can be powerful here,& he says
&Relational cases are more frequent, more human and more complex
They can require empathy, persuasion and complex thought
Sometimes a customer doesn&t know what the problem is — &it just not working&.&Other times are sales opportunities, which businesses
definitely don&t want to automate away (AI isn&t great at persuasion)
And some specific industries, e.g
emergency services, see the human response as so vital that they refuse automation entirely
In all of these situations, AI which augments people, rather than replaces, is most effective.&We see work in customer service being
transformed over the next decade
As automation of simple requests becomes the status-quo, businesses will increasingly differentiate through the quality of their human-touch
Customer service will become less labour intensive, higher skilled work
We try and imagine what tools will power this workforce of tomorrow and build them, today.&On the ethics front, he says customers are always
told when they are transferred to a human agent — though that agent will still be receiving AI support (i.e
in the form of suggested replies to help &bolster their speed and quality&) behind the scenes.Ultimate.ai customers define cases they&d
prefer an agent to handle — for instance where there may be a sales opportunity.&In these cases, the AI may gather some pre-qualifying
customer information to speed up the agent handle time
Human agents are also brought in for complex cases where the AI has had difficulty understanding the customer query, based on a set
confidence threshold,& he adds.Kainulainen says the seed funding will be used to enhance the scalability of the product, with investments
going into itsAI clustering system
The team will also be targeting underserved language markets to chase scale — &focusing heavily on the Nordics and DACH [Germany, Austria,
&We are building out our teams across Berlin and Helsinki
We will be working closely with our partners & SAP, Microsoft, Salesforce and Genesys — to further this vision,& he adds.Commenting on the
funding in a statement, Jasper Masemann, investment manager at Holtzbrinck Ventures, added:&The customer service industry is a huge market
and one of the world largest employers
Ultimate.ai addresses the main industry challenges of inefficiency, quality control and high people turnover with latest advancements in
deep learning and human machine hybrid models
The results and customer feedback are the best I have seen, which makes me very confident the team can become a forerunner in this space.&
