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30SecondsToFly

A.I. automation for travel call centers.

USA, New York
Market: Artificial Intelligence
Stage of the project: Operating business

Date of last change: 13.12.2019
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Idea

30SecondsToFly’s technology Claire provides A.I. driven workflow automation for travel call centers. Claire doubles profit for travel management companies by automating their agents’ most repetitive tasks. 30SecondsToFly goes after the $1T corporate travel market, their clients have a total turnover of $21B.

Current Status

Revenues in 2019: $140k
Signed clients with a total of $21B annual transaction volume
Clients signed: 7
Client live: 1
Clients going live in Dec: 2
Clients going live in Jan: 2
Clients going live in Feb: 2

Market

30SecondsToFly provides the “self-driving technology” for 23,000 TMCs to compete and thrive. 30SecondsToFly goes after the $1.3T corporate travel market. Primary target segment are english speaking TMCs with more than $200M in annual transaction volume who have our target technology profile*. There are ca 50 TMCs in the primary target segment turning over $150B per year.

*target tech profile:
Profile management system: Umbrella/Sureware,
GDS: Amadeus/Sabre,
Mobile app: Mtrip/Manticpoint
Mid-office system in place

Problem or Opportunity

Travel management companies (TMCs) are seeing shrinking margins due to expensive workforce (~80% of revenues, travel agent salary increased 10% from 2018 to 2019) and decreasing commissions. Now, they face an acute threat from new, tech-driven TMCs entering the market. New “Tech TMCs” are not built around human agents but around automation technology. They have raised in total more than $1B in funding to build a “Tesla” for corporate travel, operating at lower cost and providing better traveler experience.

Solution (product or service)

30SecondsToFly provides A.I. driven workflow automation for travel call centers. Their technology "Claire" is a technology layer travel management companies plug into their existing infrastructure to compete against their new tech-driven competitors. Claire automates many of their travel agents most repetitive tasks (e.g. gathering of parameters, fare optimisation) and helps their agents perform their tasks on average 52% faster.

Competitors

Mezi - acquired by Amex in 2018
Lola - in exclusivity with AmexGBT since 2019
Pana - pivoted to HR/guest travel in 2018
HelloGbye - bad reputation among customers (some of our clients were with them before)

Advantages or differentiators

- Team is highly specialised at the intersection of machine intelligence x deep travel tech (talent with expertise in both is extremely difficult to find).
- Trained our algorithms with more than 20k curated traveler interactions and iterated our technology for 3+ years until reaching current speed and accuracy:

Narrow natural language engine for the flight and hotel booking domain: response time < 1 second + accuracy 96%
Recommender systems response time less than 20 seconds + accuracy 85%

Finance

Revenues 2019: 140k (to date)
For TMC clients of avg $200M annual transaction volume:
CAC: $43k
Avg ACV: $149k
LTV: $745k (assuming 5 years retention)

ARR in June 2020: $1M
ARR in Dec 2020: $3M
ARR in June 2021: $17M
ARR in Dec 2021: $22M

Business model

Revenue model: Saas + transactional model
1.3k monthly Saas fee that includes 500 transactions + 5 agent logins
after that:
- $2-3 per transaction
- $100 per agent login
+ implementation fee: $5-20k
+ priced customisations

Money will be spent on

54% R&D
18% Sales
8% Marketing
10% G&A
8% Ops&HR
2% Finance

Offer for investor

Are going to give up 10% equity for $1.5M round.

Team or Management

Risks

Implementation + ramp up cycle with large TMCs is extremely long (for our largest clients 18 months, because we have to wait for their tech teams and decision makers). Being able to match the ramp up cycle with generation of metrics + fundraising is challenging.

Risk analysis see here: https://docs.google.com/document/d/1L5123r85BEIGSCBCj6nSYAhRLs8lPd_ZTNa_BbKY8Xk/edit?usp=sharing

Incubation/Acceleration programs accomplishment

NYU Summer Launchpad 2014, New York
Cockpit Accelerator, 2016, Tel Aviv

Won the competition and other awards

NYU InnoVention Award 2014 (winner in software category and overall winner of competition)
General Catalyst Award for Travel Innovation 2019 (winner)

Photos

Photo 1 - A.I. automation for travel call centers.
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Idea
Current Status
Market
Problem or Opportunity
Solution (product or service)
Competitors
Advantages or differentiators
Finance
Invested in previous rounds, $
Business model
Money will be spent on
Offer for investor
Team or Management
Mentors & Advisors
Lead investor
Risks
Incubation/Acceleration programs accomplishment
Won the competition and other awards
Invention/Patent
Photos
Product Video