Assaia

Part
01
of two
Part
01

SWOT Analysis: Assaia

Assaia has many opportunities and strengths as compared to its weaknesses and threats whereby, among other strengths, the company has unique products and services like provision of Artificial Intelligence (AI) solution that helps to better manage operations by understanding what is happening in real time. One weakness is that Assaia has not yet started utilizing the unstructured data that other big companies are going after to fine-tune their technology.

SWOT analysis for Assaia

strengths

  • Assaia has embraced a partnership and has several partners like IATA, SITA, ADB Safegate and Amadeus among others. This partnership has supported and boosted the company's growth rapidly.
  • The company has unique products and services like the provision of AI, which helps to better manage operations by understanding what is happening in real time.
  • Assaia's focus on providing situational awareness and generating customized alerts powered by their AI technology has helped them remain competitive because the alerts enable the prevention of delays and incidents. Moreover, dangerous situations are identified such as equipment/aerobridge that has not been stowed properly, humans not wearing high-visibility vests, and foreign object debris management.
  • Since most Airports already have CCTV in place to monitor the ramp, Assaia augments this infrastructure with machine learning technology and captures a time stamp for every event that is happening during a plane turnaround, helping attract more customers to their products and services.
  • Assaia products use high-resolution time stamps to look into the future and through this, everyone knows a turn’s status and when the plane will leave the stand. Thus, resources are used more efficiently, and delays are reduced.
  • Use of this technology helps partners tremendously increase service levels.
  • Assaia deploys their technology in three stages to ensure their clients are fully conversant with the product: (1) Small-Scale Pilot, (2) Soft Roll-Out and (3) Full Roll-out.
  • By working with several airports in the world, Assaia can work with the largest US carriers.

Weaknesses

  • Assaia has not yet started utilizing the unstructured data that other big companies are going after to fine-tune their technology.
  • During their 3-step deployment, a lot of time and other resources are wasted when training their clients because they have to work in close collaboration with their customers.

Opportunities

  • If the company can adopt structured data use like the way Google, Amazon, and Facebook did, there is a big opportunity for prosperity.
  • Assaia was selected along with other three finalists to work with IAG Cargo. This is an opportunity to access the necessary resources to develop, shape and test their products working in their own offices.
  • The company has an opportunity to grow on a global scale by receiving investment from IAG’s digital fund to scale their business.
  • The United States President Donald Trump signed an order to federal government agencies to dedicate more resources and investment into research, promotion, and training on AI. Assaia, being one company in the industry, can utilize the opportunity in increased access to federal data.

Threats

  • Assaia has developed a "straightforward approach to demonstrate [their] technology" to consumers. Competitors might use the same concepts and develop superior and related products to theirs by making sure that all the weakness in Assaia's software is addressed.
Part
02
of two
Part
02

Assaia Company Analysis

Assaia is a Swiss startup company that offers an artificial intelligence solution that can help in improving airport operations. The company was founded by Max Diez in 2018. During the company's first year of operations, it was able to deliver its solutions to various international airline terminals.

FINDINGS:

ASSAIA

GROWTH

  • The company is fairly young as it was founded in 2018 and started its operations during the early part of 2018.
  • Within just a span of over one year, the company is already delivering its solutions to over a dozen airports that are located in the United States, the Middle East, Asia, and Europe. It has also scored deals with big airlines such as British Airways.
  • It also scored contracts already to install its GPU-powered solutions around several airport terminals. Its systems are already handling video streams by the hundreds.
  • Prior to this, the startup firm already worked on training its neural networks to observe the multi-year worth of airfield videos from various international airport locations.
  • Now, the company's neural web has a deep understanding on the layouts, movements, and interactions that are happening in airports.

TARGET MARKET OR AUDIENCE

KEY CLIENTS

  • Assaia's clients that are featured in its website include mostly air travel-related companies such as Toronto Pearson, Gatwick London Airport, Swissport, Finavia, EuroAirport, and British Airways.

PRODUCTS AND SERVICES

FUNDING HISTORY AND MERGERS AND ACQUISITION INFORMATION

  • The startup was self-funded.
  • The company is also one of the finalists in International Airlines Group's (IAG) "Hangar 51 startup program."
  • The innovation program is helmed by IAG and its partners, IAG Cargo, Avios, and British Airways.
  • Assaia will undergo an immersion program with the AIG Cargo operations team coaches to enable the company to get the needed resources to improve its solution.
  • At the end of the program, the company will get a chance to present its improved solution to a panel of investors and key leaders.
  • This will open up a chance for Assaia to get investments from IAG's "digital fund" that can help in expanding the business further.

POTENTIAL COMPETITORS

  • Assaia's potential competitors in the airport operations solutions space include the following: Skyspace, Matternet, Dronamics, Avision Robotics, and Connect Robotics.
  • Other competitors that are also offering similar AI airport operation solutions include the following: Emu Analytics and Mobilus Labs.
  • Veovo also provides similar AI-powered innovation that can potentially improve airport operations.

YOUR RESEARCH TEAM APPLIED THE FOLLOWING STRATEGY:

We started our research by looking for the requested information on the Assaia company. We looked for the specified information in the company's website, in technology-related sites such as Wired, Tech Crunch, The Verge, Techstars, Apex, Nvidia, Transmetrics, and others; business-related sites such as Cox, Bloomberg, Forbes, Reuters, and similar sources; company directory sites such as Hoover, Crunchbase, Pitchbook, Money House, and similar sources; press release reports such as those from Cision, Newswire, and others; media outlets such as CNN, CNBC, and similar sources; consulting sites such as PWC, Deloitte, and other relevant sources. Based on this search approach, we were able to find the company's background, target audience, key clients as featured in its official site, some limited growth history data, a few insights on funding, some potential competitors, and other snippets of information. However, we were not able to find any details on mergers or acquisitions that the company got involved in.
Given the scarcity of information found, we looked for more data about the company by searching for interviews, surveys, or reviews about its operations. We hope to uncover insights and any information about tie-ups, collaborations, and acquisition partnerships that might help in deriving the required data. However, we were not able to uncover more information about the company and any related information on partnerships or acquisition transactions. What we found are just the same data that were obtained using the direct search strategy above.
Since the solution being offered by the company revolves around the airline industry, we looked at any reports from various airline associations such as the IATA, IAG, and others. We hope to find any reviews or evaluation done by these associations that we can use to further enhance the information found and uncover any hints on mergers or acquisition deals. However, the information found is limited and already similar to what we uncovered in our earlier search. We also were not able to find any data regarding any mergers or acquisitions involving the company.
We have concluded that the reason why the information is limited and M&A deals are not found, could be due to the relatively young age of the company. Assaia's founding date is 2018 and is still on its first year of operations. There might be more information available in this linked report from Money House but the data is behind a paywall.
Based on these search strategies, we have provided the available findings in the section above.
Sources
Sources

From Part 01
Quotes
  • "Our machine learning algorithms consume the generated timestamps together with additional relevant data sources. Based on this data it predicts the timing of key events during the aircraft turnaround process, such as off-block, pushback ready, etc."
Quotes
  • "The companies that mastered the 20% structured data prospered."
Quotes
  • "We are looking forward to working alongside Mobilus Labs, Emu Analytics and Assaia over the next 10 weeks to unlock opportunities and enhance our customer experience."
Quotes
  • "The Swiss startup Assaia is aiming to reduce the number of delayed flights and improve turnaround time for both cargo and passenger flights by changing how ground crews and airports operate."
Quotes
  • "Trump to sign executive order to prioritise and promote artificial intelligence."