This AI personal assistant took 3 years and millions to build — it completely fooled me

Dennis Mortensen

Dennis Mortensen, founder
and CEO of

A few weeks ago I was emailing Tom Blomfield, the CEO of startup
bank Monzo, to arrange lunch. He passed me over to his assistant,
Amy Ingrams, by CCing her into an email.

Amy and I exchanged eight emails fixing up a date and then
another five when Blomfield had to rearrange. Only then did I
spot something odd in Amy’s email signature: “Artificial
intelligence for scheduling meetings.”

It turns out that I had been talking to an algorithm the whole

“I’m very happy to hear not that we’ve fooled you but that we’ve
created a design that felt so natural that you probably said
‘thank you’ or ‘would you be so kind’ or something similar,” its
creator, Dennis Mortensen, told Business Insider. “That, I think,
is a testament to the design success of the agent.”

Mortensen is the founder of, the New York startup that has
developed Amy and her male counterpart Andrew Ingrams (Their
initials are AI.) The virtual assistant does one thing and one
thing only: arrange meetings.

“We’re not trying to recreate Siri or Google Assistant, we’re
trying to make this one agent — Amy, and/or Andrew — which upon
being asked can make sure that the three of us end up on this
phone number at this time,” Mortensen told BI (’s PR manager
was the third person on the line.)

‘It’s very easy to imagine but it’s very hard to execute on’

Mortensen had the idea for Amy/Andrew after selling his last
company. He was reviewing an old diary and realised he had 1,019
meetings in 2012 and had rescheduled 672 times.

Getting a computer to arrange your diary is harder than it
sounds. Mortensen says: “We’re about 90 people who’ve been
working on it for 3 years. That might come as a surprise but it’s
one of those things where, similar to a self-driving car, it’s
very easy to imagine but it’s very hard to execute on. We’ve just
invested the time and effort into it.”

It is an expensive project too. Since launch in 2013, has
raised over $35 million from investors including Japanese
telecoms giant SoftBank and FirstMark, a New York venture capital
firm that has backed companies like Pinterest, Netgear, and
Shopify. Its most recent round was in April this year
when it raised $23 million.
xai pain_solutionHow

Mortensen believes can justify the big investments and
become a company on the scale of Slack or Dropbox.

“Not a single person in your office doesn’t do meetings,” he
says. “Even the most hardcore engineer does meetings. Not a
single person says they love setting up meetings, they love that
ping pong back and forth. They hate it.”

Sean Masters, the
founder of on-demand project and staffing platform
, told BI: “Scheduling meetings is just remarkably
inefficient. She [Amy] just takes that away and it makes me more

“I’m a bit of an advocate of her. She’s actually got a bit of
sass. One of my project managers has rescheduled a meeting with
me three times. Amy responds saying she wants to reschedule this
meeting, again.” (Masters and I weren’t meeting to discuss
or connected by the company — the praise was spontaneous.) offers a basic, free version of its service to individuals,
letting them schedule up to 5 meetings a month, and recently
launched a professional edition for the self-employed, costing
$39 a month. The plan is to offer a business edition for teams
next year.

Hundreds of thousands of people have used the system to date,
Mortensen says, and millions and millions of emails have gone
through the system. Masters estimates that using Amy saves him at
least 3 hours of email admin a week.

‘There’s still ambiguity and we’re still training on that’

There was controversy surrounding the company earlier this year
when a Bloomberg article in April
claimed that much of the work involved in the emails was done by
a team of “AI trainers” who were “hiding” behind the service.

Mortensen insists the author got the wrong end of the stick.
Humans are not secretly drafting the emails but are guiding the
system to help it get smarter.

“If you look at what Uber did when they put about 30
[self-driving] vehicles on the streets of Pittsburgh — in every
single one of those self-driving cars, there’d be two Uber
employees,” he says. “One is an engineer and one to override the
cars prediction of what to do next — a.k.a. the trainers. That is
how you move from a situation where only humans ride cars to one
where only machines drive cars. If you think of nothing else, you
should think of that analogy.”

xai office’s New York

Emails that enter the system are broken down into “tasks” for the
algorithm to look at. Amy or Andrew then make a guess at what is
being said and the AI trainers either confirm or reject the
conclusion. This is how the algorithm learns.

Mortensen says: “An AI trainer is sitting at a console saying I
agree what the machine labelled as Wednesday is correct. I agree
that 4pm is indeed a time reference, correct. Or if someone says
‘have a good weekend’ you need to say that’s not relevant. If the
machine thinks it is relevant, you have to say that is incorrect.
Some things have been fully automated and no human will look at

The writing side of the system is “100% automated,”
Mortensen says, and the “vast majority” of the reading side does
not involve human supervision. It is only when complex phrasings
or unusual circumstances arise that humans step in.

Mortensen gives an example: “Our ability to work out if you want
to cancel a meeting is not fully solved. Sometimes we have a very
high competence level and sometimes we won’t because people are
too friendly. You would say I would love to chat today but things
have taken a turn, we should get a coffee in the future — that is
you being kind about saying the meeting is cancelled. That is
tricky for a machine.”

Monzo’s Blomfield told BI: “It’s really great for one-on-one
calls and meetings. It’s saved me a bunch of time. It’s not yet
perfect when there are multiple participants or a human assistant

Mortensen says: “There’s still ambiguity and we’re still training
on that.”

‘We either solve this, or we die trying’

Of’s 93 employees, 39 are AI trainers. All are based at the
company’s New York offices, on 25 Broadway. A consequence is that
my colleague Lara O’Reilly tried out the service in July 2015

she noticed that often emails from Amy would only be sent in the
afternoon in London — i.e. when New York woke up. (She noted at
the time that the experience was also “far from seamless.”)

Mortensen insists this is no longer the case.

He says: “The system today runs 24/7, 365 and we have a median
response time of 9 minutes today. The system is very different
today to what it was a year ago or even earlier in 2016. The
response time we’re running with, it’s obvious we do more emails
at higher accuracy, fully automated, without any verification.”

Masters, who began using the service a few months ago, says there
were “a couple of teething issues by they’re just learning.” He
says he would have had the same issues with a person — he would
have to get a sense of how they work and they would have to get
used to him. Otherwise, he has nothing but praise for the

Ultimately, the goal is to do away with the AI trainers
altogether and have Amy and Andrew talking directly to each
other, arranging meetings for people behind the scenes.

Mortensen says: “We are making a bet on this being something we
can turn into a completely machine-driven process. We are in very
good shape and the vast majority of the conditions that we do are
fully automated.”

He adds: “We have no plan B. There is no outcome of this venture
where we are a semi-outsourced setting. We either solve this, or
we die trying.”

from SAI