There are thousands of satellites operating and revolving around our planet Earth (apart from inter-planetary missions) some with single modality and some with multi-modality payloads. We have our pathways that began with innovations in natural sciences with organisations (including ISRO, NASA) while curating the scientific observations and deeper insights from the instruments that are orbiting around planet Earth and from instruments that accomplished inter-planetary journey. With our first team's first hand exposures in handling the usecases in diverse applications with the team members from national space agencies and private players, we realised that the high throughput data acquition strategies are failing and instead of becoming an asset it is bending towards a liability in the absence of strategies that are needed at the time of designing, integrating and putting the payloads in space with a lot of aspirations but also a lot of internal-biases, apart from the challenges of not having seamless data ingestion and realtime analytical pipelines.

Hence our focus is not about that we need more data, more details, more technologies and more computational resources, rather it is about lesser but precise-sensor modelling, integrating, mounting (degree of freedom for acquisition), uplinking and downlinking plan(data acquisition), algorithms that demands lesser computational resources for real time assessment and hence more specificity with a sense of responsible decision making. The characterisation of input (incident radiations) vs output (measured radiations), in both quantitative and qualitative dimensions require an inter-disciplinary approach for improved target characterisation strategies and more robust allied business model. Mapping and linking the precisely the dynamics with an allied kinetics and deriving an operationally reliable pattern still need huge optimisation.

At Vraisense our aim is enabling our partners the technical aid in making a well defined and purposeful synchronisation between the end-users specific needs allied to their science-based hypothesis from data and users responsible for hardware-based multi-modal technology & its implementation of observing the actual phenomenon. There are crucial valuable inputs as well as issues that exist at the interface of these nodes and need to be address with a very comprehensive approach for scientifically observing and gathering, analysing the phenomenon with efficient signal-integrity in place. We collaborate on bridging these gaps through transdiciplinary expertises and first hand exposures that enable better options for both basic science-experts as well as for technology and data providers, to opt for. Ensuring high standards of imaging-oriented mechanisms, processes, pipelines and allied consultancies associated with non-invasive approaches for applications such as remotely performing chemical, biological and spectrometric analyses on scenes taken from payloads mounted on aerial- or space-platforms. The challenges are with the specificity and preciseness. And hence the role of allied collective innovations.

With more comprehensive and innovative strategies in place, we help our partners in developing data-driven strategies that significantly help in deciding when and which sensor- and data-resolution is more relevant and suitable within the constrained situations. Our exposures made us realised that even when we have all resources in abundance and in place it won't guarantee that we are performing and using resources in optimise manner. Redundancies are contributing more in consuming our critical resources, time and energy, than absence of them, ultimately tending us towards a state of literally empowered but logically inefficient at high-level.

At VraiSense, we are acting at the core of the research that multiplexes efficiently the science, technology and enbling the robust mechanisms and measures that helps basic science experts in specialised fields, such as resources mapping and realtime space intelligence. Starting with the quantification of mineral assemblages, quality and abundances of interest (e.g. copper and lithium - some of the major consituents in battery-powered energy sources), our use cases and allied customised automated tools have been utilised and validated for multiple appliations such as pollutants identification and emissions characterisation; water-, snow-, air-quality assessment for overall environmental compliance; quantification of soil and plant-specific stresses and nutrient-deficiency; early-phase plant-pathogen interaction, disease detection and bioefficacy of pesticides at canopy-clustering level; improving space-based sensor-design, uplinking and downlinkng planning, intelligence, surveillance, and reconnaissance, quite efficiently and through need specific data-lens. We help our customers to see things through some deeper technology- and data science-lens. Contact us to learn more about how we can become the complementry partner in your mission.

We remain stick to the standards of technological-viabilities and robust data gathering mechanism as that forms the scientific basis of the signal integrity with end user's hypothesis, and hence we collaborate on improving the characterisation of radiation-target-detector with a bit more closer and deeper insights for significantly improving the observation approaches and allied target characterisation. The optimisation strategy needs comprehensiveness and inter-disciplinary mindset, that essentially requires a big shift in thinking how we think and plan before we start acting.

We collaborate on technology-driven scientific and innovational approaches that assist products to match and meet the scientific values and efficiency-based principles, throughout the product life cycle. Collaborating on better mapping the toxicological pathways with a focus on improving accuracy and precision. Seeing the potential challenges posed by the abundance mindset, we critically need a balance approach and hence we are there to act. We carry a laser-focused approach to justify what, when, and why which less is more and which more is less important for solving the purpose-scientificlly and digitally.

Our primary aim is to help customers and partners in the synchronising their conventional approaches of observing the Earth-resources with innovative and standardised aerial- and space-based digital processes. Together everyone achieve more with lesser resources and within lesser time. Please feel free in connecting the dots allied to your use case.