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Our Story

Our founding team first met at the University of Oxford. Inspired by each other's unique stories, goals and our collective curiosity and passion for space and technologies, we quickly decided to join forces to build space-tech solutions to "Make this World a Better Place".

Now we are taking our next important step in our mission and we invite you to join us on this exciting ride as we kick start our "F&F" fundraiser. We hope you enjoy the following information.

Black Sky

Advanced Machine Learning Edge Computing Solutions for Space

Fundraising Round 2022 - TARGET USD $250,000


Progress chart


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First Mission Signed

First Space mission scheduled for Q2 2023

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Partnerships Established

2 LOIs & in discussion on 4 additional space missions

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Strong Team

Team of 14 with strong business, technology, execution experience and domain knowledge in Space & AI.

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Vast Support

Part of University of Oxford and alumni of prominent space and defense accelerators in the US and UK




Today many events and object detection are done with space analytics, but there are significant delays resulting in billions of dollars of losses and lives.  



Eliminating the bottleneck of raw data downlink by performing data processing and generating analytics in-orbit (aka as Edge Computing in Space). Only useful analytics are sent back to the ground.



ORBITFY, a product suite of proprietary advanced ML applications that can generate near-real-time analytics in orbit and deliver them through our platform for many use cases.



Signed contract with Exo-Space to provide near-real-time space analytics for fishing vessel detection. Space deployment is scheduled for Q2 2023.


LOIs with two partners, including a key satellite operator and an edge computing service platform provider. 

Advanced discussions with 4 partners to perform space demonstration in the next 6-8 months.

Winner of the Global Gravity Challenge in Space AI, hosted by industry leaders Deloitte and AWS. 

Active and contributing member of leading communities such as Oxford Space Initiative and Edge Computing in Space Alliance. Alumni of prominent space accelerators, including the UK Space Agency, Starburst Aerospace, and the Catalyst Campus.



End-Users of Space Analytics - especially those that need near-real-time analytics with minimal latency to act on time-sensitive events.

Satellite/ Space Assets & Infrastructure Operators & Government Agencies -  stakeholders or responders to space situational awareness such as debris management, autonomous operations, and object detection in space.


We plan to generate revenue by:

1) Selling SaaS analytics to B2B users from various non-space industries who need quick satellite-generated analytics and;

2) Licensing our AI/ML edge applications to satellite companies to run on their infrastructure.



Approx. Market Size $51B


Offering unparalleled near real-time analytics for many use-cases that current ground-based solutions can’t match.


Our team has deep and holistic experience in building and delivering cutting-edge technological products. In addition to technology, we have built and run startups, and are fluent in many business aspects. Our advisors are long-time space and defense professionals.


Focus on deploying our first space mission in Q2 2023 and building out our product and access to necessary space infrastructure through additional missions within the next 6-8 months. Onboard customers starting 2H 2023.


Space demonstration and mission deployment of product ORBITFY by mid-2023. Scale up on serving end-users with analytics.

Media Mentions


Combating Illegal Fishing with Space-Based Edge Computing


Global Gravity Challenge Awards


Oxford Saïd pitch competition

Catalyst Accelerator.png

Catalyst Government Boot camp


Today many events and object detection are done with space analytics, but there are significant delays resulting in billions of dollars of losses and lives.  

Nowadays, we expect to receive real-time insights and analytics on the most important and crucial events taking place on Earth. But this is only possible for a fraction of events where ground sensor coverage is good. The only way to reach a truly global scale of real-time intelligence is by using Space analytics. 
But today’s space analytics are slow, not real-time, leading to significant delays in actionable insights reaching the end-users to respond to time-sensitive situations. These include detection of natural disasters like forest fires, vast floods, illegal activities on ground/water, deforestation, defense ISR (intelligence, surveillance and reconnaissance) activities, and many other use cases. This results in billions of dollars of losses and lives.
Little Place Labs wants to address this problem. 
Satellites in space watch the Earth using camera sensors and send raw imagery to the ground for processing. Each day satellites send over 10 million raw photos down to Earth. Images are being created faster than they can be sent to the ground and be processed [1]. In the next 3 years, satellite cameras will produce images at a rate of 1 gigabyte per second [2*], which represents 10 times the amount of data generated from one sensor than is generated from all satellites in operation today. It can take hours before raw images are sent to the ground, processed into analytics, and then delivered to the end user. This delay, also known as latency, has major impacts. Imagine if the fire department can be notified and respond to a fire within a few minutes from its onset, rather than after a few hours, when the fire is spreading and burning down 50 acres every minute?

*User input required to view source. Statement takes place at 29:30.


Our solution is to reduce delays by performing in-orbit data processing and delivering near-real-time space analytics

Near real-time space analytics are the only way to monitor large-scale, time sensitive events. Little Place Labs is building solutions to provide near real-time space analytics at reduced cost and flexibility. 
Our suite of advanced machine learning software applications, called “
Orbitfy”,can be deployed on satellites, and are designed and optimized  to work in the constrained environment of space (limited electricity supply and processing power). In-orbit data processing is performed as soon as raw data is captured directly from onboard sensors and is analyzed. Our applications and machine learning algorithms can be updated anytime in orbit, providing continuous guarantee of accuracy and flexibility to adapt to changing markets and customer needs. Instead of downlinking all of the raw data, we would only send useful processed insights to the ground, which is much smaller in size and hence more quicker.
We can reduce the size of the downlink data by a factor of
10,000x, and deliver the analytics within minutes rather than hours and days. Without the unnecessary downlink, we can help reduce the cost by 5x for our end-consumers.

Edge Data Processing


Orbitfy - software suite that can generate and deliver critical space analytics in near real-time

Our team has experience designing, building and delivering software products and services. 

Product Opportunity - Our product suite “Orbitfy” comprises of 3 key components:

Orbitfy Product Map

Orbitfy Prep - in-orbit pre-processing engine helping customers within satellite and sensor operators pre-process space raw data from a variety of sensors, while in-orbit, into many usable and standardized formats. 

Orbitfy Edge - powered by our proprietary advanced ML models, this is the core analytics engine running in space that transforms raw data into useful analytics

Orbitfy View - targeted at end users of insights, this SaaS analytics platform not just delivers near real-time space analytics to end users (via Web or API) but allows users to schedule new tasks from a list of end-use modules.

We do not plan to own and operate our own satellites. Our vision is to leverage partners that offer Satellite-as-a-Service by renting out satellite time (more details in the Partners section).


Transactional Service Opportunities - in addition to the Orbitfy product suite, we have been approached to build customized solutions for space-for-space use cases. These use cases align well with our core competency and we continue to be open to catering to such requests as an additional revenue stream.

Similar to what the SpaceX Dragon Capsule uses when autonomously docking to the International Space Station (ISS), we are looking to develop smart software that will run on edge AI devices providing flight safety for any satellites or spacecrafts that might need to:

  • rendezvous and dock (e.g. MEV-1 mission)

  • perform on-orbit inspection missions (e.g. Restore-L mission)

  • remove orbital debris (e.g. ClearSpace-1 mission)

ren mod 3


First Space mission in Q2 2023 with potential 4 in the coming 6-8 months. Established strong connections within the Space and Defense communities.


In June 2022, LPL signed its first customer contract with Exo-Space to provide the ML applications that would generate near-real time space analytics in orbit, for detecting Illegal fishing activities along the coast of Thailand. In collaboration, the companies are scheduled to launch the satellite mission in early Q2 2023 to a 500-km sun-synchronous orbit.


Little Place Labs has been establishing network relationships with satellite operating companies to utilize the Satellite-as-a-Service model (“share ride” of satellites) - where LPL can deploy our applications onto many satellites without having to build our own. Satellite shared rides are a relatively new yet booming business model. 


We are currently in discussion with different partners regarding 4 space missions and a number of demonstrations in the next 6-8 months. We have executed LOIs with ExoSpace, Exodus Orbital, and EnduroSat, and expect to be at LOI stage by mid Q4 with at least 7 additional players (across US, UK and Europe).


In 2021 LPL achieved the first major milestone in being selected as the champion of the global Gravity Challenge 03 organized by Deloitte and AWS. We successfully went through the end-to-end process of gathering and training of raw datasets, building and testing of our wildfire detection models using AWS services. Even with a limited dataset, we achieved 88% accuracy with our wildfire detection models. 

In 2022, we were successfully selected and completed prominent accelerators, including the Explore Program, funded by the UK Space Agency, and the Starburst Aerospace Accelerator in collaboration with UCLA.

US Defense

Little Place Labs is now registered as an eligible federal government contractor. With a vision of working with the US DoD, we participated in and completed the Catalyst Government Bootcamp. We connected with potential customers from the DoD and other government contractors.


We have also recruited advisors who are long-time professionals in the US defense community. LPL is now a registered government contractor in the US, eligible to apply for government grants and bid for contracts.


$106B Total Addressable Market Size

$51B Approximate Serviceable Available Market Size

Little Place Labs has three customer segments corresponding to three different market segments which coincide neatly from the technological capability perspective:

Market Segment
Market Size
US DoD, UK MoD and other NATO countries
TAM = $12B; SAM ~ $7B
SAM focuses on NATO countries' ISR needs. NATO countries defense department budget for ISR substantially stands out.
Space For Space
Stakeholders in space situational awareness topics, including Satellite Operators, Spacecraft Manufacturers, Government agencies
TAM = $24B; SAM = $5B
SAM is the market covering NATO countries focusing on non-hardware services.
Space For Ground
End ground user of space analytics (aka Earth Observation or EO users)
TAM = $70; SAM = $38B
14.6% CAGR YoY growth for next decade. SAM is the market covering NATO countries.

Market Segments

Space for Ground (Earth Observation):


The global market size was $70B in 2020 and is expected to grow at 14.6% CAGR. This is further comprised of Satellite Big Data = $22B, EO Value-Added Services = $8B, EO Information Products = $27B, EO Big Data Analytics = $10B, Big Data Analytics = $3B. Our products will be marketed with NATO and allies, and this will reduce the SAM to around $38B. 


Space for Space:


The global space situational awareness and In-orbit processing market size is $24bn in 2020, some of which is hardware development, creating a significant opportunity and need for software solutions. The US Department of Defense has also identified this as one of the top national security priorities. To cover non-hardware services for NATO and allies, the Serviceable Available Market (SAM) is expected to be $5B. 



The market size in Defense can be deferred by the budget spending. For example the US Space Force alone (not including other branches within the US Department of Defense, which are all potential users), the 2023 budget is US$24.5bn, and of such, US$3.6bn is directly related to the procurement of satellites and satellite services. The TAM covers the budget of the NATO countries and is extrapolated to $7B. 


Source: NSR’s Global Space Economy, 2nd Edition

Customer Segments


End-users of the analytics


Little Place Labs focuses on these sets of customers who need near-real-time analytics with minimal latency to take action on time-sensitive events. For example:

  1. Natural Disaster Detection - Fire department, Forestry Department, Coast Guards, Insurance Companies

  2. Financial Services/ Asset Optimization - Trading shops, banks, and infrastructure operators like shipping ports, roads and railways.

  3. Defense - Department of Defense, and commercial contractors.


Satellite/ Space Assets & Infrastructure Operators & Government Agencies:


These customers own or are responsible for operating space assets and infrastructures. Specifically those that are involved in space situational awareness such as debris management, autonomous operations, and object detection. Our advanced software will be the driver of such hardware. Users can include:


  1. Defense

  2. Space agencies

  3. Commercial hardware and robotics companies

  4. Debris management companies

  5. Autonomous satellites and space object companies

Business Model

A combination of SaaS-based Subscription and Transactional Service Offering

Business model 1

Applies to the space-for-space segment where Satellite Operators are LPL’s customers. LPL will sell the Orbitfy suite of services to satellite operators by licensing the software. 

rev mod 1

Business model 2

Applies to the space-for-ground segment where end ground users of space analytics are LPL’s customers. LPL will provide space analytics in various ways, including as a SaaS subscription model, or as a transactional service offerings.

rev mod 2


Offering unparalleled custom use-cases and automated platform that our competitors can’t match

Little Place Labs is a pure software player and there are very few like us. Our competitors are players who provide similar capabilities to end users - either software applications that can perform edge computing on satellites and spacecraft or provide near real time insights for the use cases. 
Players like Palantir could be our competitor if working on the same use case but very well be our collaborators - we can provide our analytical software which utilize Palantir’s data platform and add on to their range of analytics offerings. 
There are also other companies that focus on specific use cases - but they are mostly ground based and will not be able to keep up in speed, cost and efficiency. 


Only recently a few companies have shown intent in building similar capabilities but they are small and are based in different geographies catering to different end-user segments. 

Some examples include:

  • Palantir

  • AIEO (Italy)

  • Shape Shift (Japan)

  • Mobius Labs (startup from Germany)

  • Lulav Space (startup from Israel)


Perfect founding trio of Business + Technology + Execution supported by deep domain experts

Our founding team met at the Executive MBA program at the University of Oxford. The co-founders form a strong triangle of business, technology and execution, and are supported by a team of domain experts in AI, Space and Defense.

Bosco Lai (CEO) - 18 years in various leadership roles in a global investment bank, executive team at energy data analytics firm, venture partner at leading climate tech VC, and consulting. Bachelor in Electrical Engineering, McMaster University and Bachelor in Life Science, University of Toronto.

Gaurav Bajaj (CTO) - 18 years in consulting and start-ups building software tech products in FinTech. Gaurav holds a Bachelors of Engineering (Electronics & Communication), from Bangalore, India.

Liuba Sergeeva (COO) - 15 years in consulting across multiple sectors, focusing on solution delivery and operations across Europe. Masters in International Economics, Taras Shevchenko National University.

Our core team consists of nine people, from deep domain knowledge in space (satellite engineering, remote sensing, earth observation), data science (AI/ML, deep learning) and other critical business functions (marketing and communications). The AI team is led by Sebin John who holds a masters in AI and Machine Learning from University of Lugano, Switzerland. The geospatial team is led by Mohan Raju, who holds masters in Geoinformatics and remote sensing from the University of Twente, Netherlands. 


We also have expert advisors that include:


Marisa Lightfoot - US Defense Personnel with a background in space or intelligence arena and experience as a Government Program Manager at NGA and CIA. 


David Brill - Experienced US Pilot and Military Officer with over 4000 hours in Fighter, Trainer, Reconnaissance and Commercial aircraft, TS/SCI focused on ISR and PED. 


Syed Shah - Led several product development projects in aerospace along 14+ years in both start-ups and established aerospace industry leaders such as Planet and Spire.

Daniel Davies - Building satellites for more than a decade at Israel Aerospace Industries (IAI) and now at Astroscale.


Space demonstration of product Orbitfy by mid 2023. Serving end users with analytics by the end of 2023.

The team at Little Place Labs will make use of the investment to demonstrate our product Orbitfy on a satellite in space. Today the product’s technology readiness level stands at TRL 4. With the investment we will take the technology readiness level to highest TRL 9 by delivering the first contract. Know more about TRL levels here.

The use of funds for this fundraising round is estimated below. Most of the funds will be used for product development including advancement of our space demonstrations, and business development including customer outreach.

Use of Funds

Beyond that we are planning to raise a $5 million seed round in Q2 2023 in line with completing our first space mission. We projected to start generating revenue from 3 clients by the end of 2023, and reach $28 million of revenue by 2027. At that inflection point, we would be in scale mode and aim at growing our revenue to $73 million by 2030.



Little Place Logo

Little Place Labs - Making Satellite Smarter

We focus on building sustainable and scalable space-based technological solutions that can be widely applicable, for the benefit of humanity and to make this world a better place.

Little Place Labs strives to become the leader in leading-edge computing software for many types of space infrastructures (satellites, robotics, space habitants etc.) and many different end-use market segments, including space-for-ground and space-for-space applications.


The next couple of decades are bound to see innovation in space infrastructure and we aim to provide advanced AI, Blockchain, quantum computing and other capabilities making the solution truly interplanetary.

  • Website -

  • Team Size - 14

  • Founding Year - 2020

  • Company Type - Private, registered in the US (2022) and UK (2021)


Documents related to fundraising to be released shortly.

Although forward-looking statements contained in this presentation are based upon what management of the Little Place Labs believes are reasonable assumptions, these statements are not guarantees of future performance and undue reliance should not be placed on them. Such forward-looking statements necessarily involve known and unknown risks and uncertainties, which may cause actual performance and financial results in future periods to differ materially from any projections of future performance or result expressed or implied by such forward-looking statements.

Next Steps

We sincerely thank you for your interest in Little Place Labs. I hope you are excited about our vision and the opportunity to launch with us.

Please do not hesitate to contact us at if you have any questions or need more information. We are also more than happy to arrange 1:1 sessions.

Go Space!

Media Mentions
Business Model
Next Steps
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