Here is a recent interview with Florian Corgnou, CEO of BrainChip partner Neurobus, which was conducted in the run-up to the 12 June INPI* Pitch Contest at Viva Technology 2025, during which five start-ups competed against each other. Neurobus ended up winning the pitch contest by âshowcasing our vision for low-power, bio-inspired edge AI for autonomous systemsâ (see above post by
@itsol4605).
*INPI France is the Institut National de la PropriĂŠtĂŠ Industrielle, Franceâs National Intellectual Property Office.
In this interview, Florian Corgnou mentions
NeurOS, an embedded operating system that Neurobus is developing internally. InterestingâŚ
âCF: Traditional AI, based on the
deep learning [2], is computationally, data-intensive and energy-intensive.
However, the equipment we equip â satellites, micro-drones, fully autonomous robots â operates in environments where these resources are rare, or even absent.
So we adopted a frugal AI, designed from the ground up to work with little: little data (thanks to event cameras), little energy (thanks to neuromorphic chips), and little memory.
This forces us to rethink the entire design chain: from hardware to algorithms, including the embedded operating system that we develop internally, NeurOS.â
I found another reference to NeurOS here:
https://dealroom.launchvic.org/companies/neurobus/
MORE ABOUT NEUROBUS
Neurobus is pioneering a new era of ultra-efficient, autonomous intelligence for drones and satellites. Leveraging neuromorphic computing, an AI inspired by the brainâs structure and energy efficiency,
our edge AI systems empower aerial and orbital platforms to perceive, decide, and act in real-time, with minimal power consumption and maximum autonomy.
Traditional AI architectures struggle in constrained environments, such as low-Earth orbit or on-board UAVs, where power, weight, and bandwidth are critical limitations.
Neurobus addresses this with a disruptive approach: combining event-based sensors with neuromorphic processors that mimic biological neural networks. This unique integration enables fast, asynchronous data processing, up to 100 times more power-efficient than conventional methods, while preserving situational awareness in extreme or dynamic conditions.
Our embedded AI systems are designed to meet the needs of next-generation autonomous platforms in aerospace, defense, and space. From precision drone navigation in GPS-denied environments to on-orbit space surveillance and threat detection, Neurobus technology supports missions where latency, energy, and reliability matter most.
We offer a modular technology stack that includes hardware integration, a proprietary neuromorphic operating system (NeurOS), and real-time perception algorithms. This enables end-users and integrators to accelerate the deployment of innovative, autonomous capabilities at the edge without compromising performance or efficiency.
Backed by deeptech expertise, partnerships with leading sensor manufacturers, and strategic collaborations in the aerospace sector,
Neurobus is building the foundation for intelligent autonomy across air and space.
Our mission is to unlock the full potential of edge autonomy with brain-inspired AI, starting with drones and satellites, and scaling to all autonomous systems.
French original:
Grâce à une intelligence artificielle sobre et efficiente, Neurobus rÊinvente, entre Toulouse et Paris, la façon dont les machines perçoivent et interagissent avec leur environnement, ouvrant ainsi la voie vers la conquête des milieux hostiles. Florian Corgnou, son dirigeant et fondateur, nous...
www.inpi.fr
NEUROBUS : une IA embarquĂŠe qui consomme très peu dâĂŠnergie
Grâce Ă une intelligence artificielle sobre et efficiente, Neurobus rĂŠinvente, entre Toulouse et Paris, la façon dont les machines perçoivent et interagissent avec leur environnement, ouvrant ainsi la voie vers la conquĂŞte des milieux hostiles. Florian Corgnou, son dirigeant et fondateur, nous en dit un peu plus sur cette start-up de la Deeptech quâil prĂŠsentera Ă Viva Technology, lors du Pitch Contest INPI organisĂŠ en partenariat avec HEC Paris.
Pouvez-vous vous prĂŠsenter en quelques mots ?
Florian Corgnou : Je mâappelle Florian Corgnou, fondateur et CEO de Neurobus, une start-up
deeptech que jâai crĂŠĂŠe en 2023, entre Paris et Toulouse. DiplĂ´mĂŠ dâHEC, jâai fondĂŠ une première entreprise dans le secteur du logiciel financier avant de rejoindre le siège europĂŠen de Tesla aux Pays-Bas. Jây ai travaillĂŠ sur des problĂŠmatiques dâinnovation et de stratĂŠgie produit.
Avec Neurobus, je me consacre Ă une mission : concevoir des systèmes embarquĂŠs dâintelligence artificielle neuromorphique, une technologie bio-inspirĂŠe qui rĂŠinvente la façon dont les machines perçoivent et interagissent avec leur environnement. Cette approche radicalement sobre et efficiente de lâIA ouvre des perspectives inĂŠdites pour les applications critiques dans la dĂŠfense, le spatial, et la robotique autonome.
Notre conviction, câest que lâautonomie embarquĂŠe ne peut ĂŠmerger quâen conciliant performance, sobriĂŠtĂŠ ĂŠnergĂŠtique et intelligence contextuelle, mĂŞme dans les environnements les plus contraints, comme lâespace, les drones lĂŠgers ou les missions en zones isolĂŠes.
Quâest-ce qui rend votre entreprise innovante ?
F.C. : Neurobus se distingue par lâintĂŠgration de technologies neuromorphiques, câest-Ă -dire une IA capable de fonctionner en temps rĂŠel avec une consommation ĂŠnergĂŠtique ultra-faible, Ă lâimage du cerveau humain.
Nous combinons des camĂŠras ĂŠvĂŠnementielles
[1] avec des processeurs neuromorphiques pour traiter directement Ă la source des signaux complexes, sans avoir besoin dâenvoyer toutes les donnĂŠes dans le
cloud.
Ce changement de paradigme permet une autonomie dĂŠcisionnelle embarquĂŠe inĂŠdite, essentielle dans les applications critiques comme la dĂŠtection de missiles ou la surveillance orbitale.
Florian Corgnou, fondateur et CEO de NeurobusŠ
Vous avez choisi une IA sobre, adaptÊe aux contraintes de son environnement. Pourquoi ce choix et en quoi cela change-t-il la façon de concevoir vos solutions ?
F.C. : LâIA traditionnelle, basĂŠe sur le
deep learning [2], est gourmande en calcul, en donnĂŠes et en ĂŠnergie. Or, les matĂŠriels que nous ĂŠquipons â satellites, micro-drones, robots en autonomie complète â ĂŠvoluent dans des environnements oĂš ces ressources sont rares, voire absentes.
Nous avons donc adoptĂŠ une IA frugale, conçue dès le dĂŠpart pour fonctionner avec peu : peu de donnĂŠes (grâce aux camĂŠras ĂŠvĂŠnementielles), peu dâĂŠnergie (grâce aux puces neuromorphiques), et peu de mĂŠmoire.
Cela nous force Ă repenser toute la chaĂŽne de conception : du matĂŠriel jusquâaux algorithmes, en passant par le système dâexploitation embarquĂŠ que nous dĂŠveloppons en interne, le NeurOS.
Quel est le plus gros dĂŠfi auquel vous avez dĂť faire face au cours du montage de votre projet ?
F.C. : Lâun des plus grands dĂŠfis a ĂŠtĂŠ de convaincre nos premiers partenaires et financeurs que notre technologie, bien quâencore ĂŠmergente, pouvait surpasser les approches conventionnelles.
Cela impliquait de crÊer de la confiance sans produit final, de prouver la valeur de notre approche avec des dÊmonstrateurs très en amont, et de naviguer dans des Êcosystèmes exigeants comme le spatial ou la dÊfense, oÚ la crÊdibilitÊ technologique et la propriÊtÊ intellectuelle sont clÊs.
Votre prise en compte de la propriĂŠtĂŠ industrielle a-t-elle ĂŠtĂŠ naturelle ? Quel rĂ´le a jouĂŠ lâINPI ?
F.C. : Dès le dÊbut, nous avons compris que la propriÊtÊ industrielle serait un levier stratÊgique essentiel pour valoriser notre R&D et protÊger notre avantage technologique.
Cela a ĂŠtĂŠ naturel, car notre innovation se situe Ă lâintersection du
hardware, du
software et des algorithmes.
LâINPI nous a accompagnĂŠs dans cette dĂŠmarche, en nous aidant Ă structurer notre propriĂŠtĂŠ industrielle â brevets, marques, enveloppes Soleau⌠â et Ă mieux comprendre les enjeux liĂŠs Ă la valorisation de lâinnovation dans un contexte europĂŠen.
[1] Afin dâĂŠviter des opĂŠrations inutilement coĂťteuses en temps comme en ĂŠnergie, ce type de camĂŠra nâenregistre une donnĂŠe quâen cas de changement de luminositĂŠ.
[2] Le
Deep learning est un type d'apprentissage automatique, utilisĂŠ dans le cadre de lâĂŠlaboration dâintelligence artificielle, basĂŠ sur des rĂŠseaux neuronaux artificiels, câest-Ă -dire des algorithmes reproduisant le fonctionnement du cerveau humain pour apprendre Ă partir de grandes quantitĂŠs de donnĂŠes.
Titre
DonnĂŠes clĂŠs :
Contenu
- Date de crĂŠation : avril 2023
- Secteur dâactivitĂŠ : Deeptech - IA neuromorphique embarquĂŠe (spatial, dĂŠfense, robotique)
- Effectif : 6
- Chiffre dâaffaires : 600 k⏠(2024)
- Part du CA consacrĂŠe Ă la R&D : 70 % (estimĂŠ)
- Part du CA Ă lâexport : 20 %
- Site web : https://neurobus.space/
Titre
PropriĂŠtĂŠ industrielle :
Contenu
Enveloppe(s) Soleau :
1
English translation provided on the INPI website:
Using a simple and efficient artificial intelligence (AI), Neurobus is reinventing the way machines perceive and interact with their environment between Toulouse and Paris, paving the way for conquering hostile environments. Florian Corgnou, its director and founder, tells us a little more about...
www.inpi.fr
NEUROBUS: an on-board AI that consumes very little energy
Using a simple and efficient artificial intelligence (AI), Neurobus is reinventing the way machines perceive and interact with their environment between Toulouse and Paris, paving the way for conquering hostile environments. Florian Corgnou, its director and founder, tells us a little more about this Deeptech startup, which he will present at Viva Technology during the INPI Pitch Contest organized in partnership with HEC Paris.
Can you introduce yourself in a few words?
Florian Corgnou: My name is Florian Corgnou, founder and CEO of Neurobus, a start-up
deeptech which I created in 2023, between Paris and Toulouse. A graduate of HEC, I founded my first company in the financial software sector before joining Tesla's European headquarters in the Netherlands. There, I worked on innovation and product strategy issues.
With Neurobus, I'm dedicated to a mission: to design embedded neuromorphic artificial intelligence systems, a bio-inspired technology that reinvents the way machines perceive and interact with their environment. This radically sober and efficient approach to AI opens up unprecedented perspectives for critical applications in defense, space, and autonomous robotics.
Our belief is that on-board autonomy can only emerge by reconciling performance, energy efficiency and contextual intelligence, even in the most constrained environments, such as space, light drones or missions in isolated areas.
What makes your company innovative?
CF: Neurobus stands out for its integration of neuromorphic technologies, i.e., an AI capable of operating in real time with ultra-low energy consumption, like the human brain.
We combine event cameras
[1] with neuromorphic processors to process complex signals directly at the source, without needing to send all the data into the
cloud.
This paradigm shift enables unprecedented on-board decision-making autonomy, essential in critical applications such as missile detection or orbital surveillance.
Florian Corgnou, founder and CEO of NeurobusŠ
You've chosen a simple AI, adapted to the constraints of its environment. Why this choice, and how does it change the way you design your solutions?
CF: Traditional AI, based on the
deep learning [2], is computationally, data-intensive and energy-intensive. However, the equipment we equip â satellites, micro-drones, fully autonomous robots â operates in environments where these resources are rare, or even absent.
So we adopted a frugal AI, designed from the ground up to work with little: little data (thanks to event cameras), little energy (thanks to neuromorphic chips), and little memory.
This forces us to rethink the entire design chain: from hardware to algorithms, including the embedded operating system that we develop internally, NeurOS.
What was the biggest challenge you faced while setting up your project?
CF: One of the biggest challenges was convincing our early partners and funders that our technology, while still emerging, could outperform conventional approaches.
This involved building trust without a final product, proving the value of our approach with early demonstrators, and navigating demanding ecosystems like space or defense, where technological credibility and intellectual property are key.
Was your consideration of industrial property a natural one? What role did the INPI play?
CF: From the outset, we understood that industrial property would be an essential strategic lever to enhance our R&D and protect our technological advantage.
This was natural, because our innovation lies at the intersection of the
hardware,
with and algorithms. [There seems to be a translation error here, as the French original mentions hardware, software and algorithms: âlâintersection du
hardware, du
software et des algorithmes.â]
The INPI supported us in this process, helping us to structure our industrial property â patents, trademarks, Soleau envelopes, etc. â and to better understand the issues related to the promotion of innovation in a European context.
[1] To avoid unnecessarily costly operations in terms of time and energy, this type of camera only records data when there is a change in brightness.
[2] Le
Deep learning is a type of machine learning, used in the development of artificial intelligence, based on artificial neural networks, that is, algorithms reproducing the functioning of the human brain to learn from large amounts of data.
Title
Key data:
Contents
- Date created: April 2023
- Sector of activity: Deeptech - Embedded neuromorphic AI (space, defense, robotics)
- Number: 6
- Turnover: âŹ600k (2024)
- Share of turnover devoted to R&D: 70% (estimated)
- Share of turnover from exports: 20%
- Website: https://neurobus.space/
Title
Industrial property:
Contents
Soleau envelope(s):
1
*Soleau envelope:
en.m.wikipedia.org
The
Soleau envelope (French: Enveloppe Soleau), named after its French inventor,
Eugène Soleau [
fr], is a sealed envelope serving as proof of priority for inventions valid in France, exclusively to precisely ascertain the date of an invention, idea or creation of a work. It can be applied for at the
French National Institute of Industrial Property(INPI). The working principles were defined in the ruling of May 9, 1986, published in the
official gazette of June 6, 1986 (
Journal officiel de la RÊpublique française or JORF), although the institution of the Soleau envelope dates back to 1915.
[1]
The envelope has two compartments which must each contain the identical version of the element for which registration is sought.
[2] The INPI laser-marks some parts of the envelope for the sake of delivery date authentication and sends one of the compartments back to the original depositary who submitted the envelope.
[2]
The originator must keep their part of the envelope sealed except in case of litigation.
[3] The deposit can be made at the INPI, by airmail, or at the INPI's regional subsidiaries.
[2] The envelope is kept for a period of five years, and the term can be renewed once.
[3]
The envelope may not contain any hard element such as cardboard, rubber, computer disks, leather, staples, or pins. Each compartment can only contain up to seven A4-size paper sheets, with a maximum of 5 millimetres (0.2 in) thickness. If the envelope is deemed inadmissible, it is sent back to the depositary at their own expense.
[2]
Unlike a
patent or
utility model, the depositor has no exclusivity right over the claimed element. The Soleau envelope, as compared to a later patent, only allows use of the technique, rather than ownership, and multiple people might submit envelopes to support separate similar use, before a patent is later granted to restrict application.
...
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