Digantara’s MOSAIC architecture represents a breakthrough in space-domain awareness, enabling real-time detection, tracking, and analysis of hundreds of orbital objects simultaneously.

By fusing AI-driven sensing with orbital intelligence, it strengthens India’s ability to safeguard satellites, mitigate collision risks, and build a proprietary catalogue of resident space objects.

MOSAIC, or the AI-powered Wide Area Sensing Architecture, is designed to search, detect, and track multiple objects across orbital volumes. It transforms raw sensor observations into orbital intelligence, providing actionable insights for satellite operators, defence agencies, and commercial space actors. 

This capability is critical as the number of satellites and debris fragments in orbit continues to rise, with projections exceeding 70,000 active satellites in the coming years.

The system integrates patented space-based sensors with ground observatories, combining optical, infrared, radar, and LiDAR inputs. This multi-sensor approach ensures redundancy, reduces measurement noise, and enhances accuracy in orbital predictions.

Digantara’s proprietary orbit engine processes these inputs, generating state vectors and trajectories with minimal latency, often below five minutes. Such rapid updates allow for near real-time collision assessments and manoeuvre detection.

MOSAIC is capable of tracking objects from low Earth orbit to geostationary orbit, with expansion potential towards cislunar space. Its detection threshold is reported to be as fine as three centimetres, enabling monitoring of even small debris fragments that pose significant risks at orbital velocities.

The architecture supports revisit rates of up to eight observations per day for selected targets, ensuring continuous custody of critical objects.

Artificial intelligence forms the backbone of MOSAIC. The system employs advanced algorithms for behaviour pattern analysis, conjunction screening, volumetric monitoring, and event reconstruction. 

This allows operators to not only detect objects but also predict their future trajectories and potential threats. AI-driven analytics provide tailored orbit insights, supporting both defensive and commercial applications.

Digantara is developing satellites in the 25–150 kilogram class equipped with optical and LiDAR payloads for space-to-space surveillance.

These satellites complement ground-based telescopes, which are limited by weather, daylight, and atmospheric distortion. By maintaining custody of objects beyond the reach of ground networks, MOSAIC ensures comprehensive orbital coverage.

Applications of MOSAIC extend beyond collision avoidance. Defence agencies can use it for proximity screening, neighbourhood watch functions, and safeguarding strategic assets. Commercial operators benefit from lifecycle analysis, insurance risk assessments, and operational support.

Regulators gain tools to enforce compliance with international treaties, such as the Outer Space Treaty, which mandates continual supervision of national space activities.

The architecture aligns with India’s broader push for self-reliance in space situational awareness. By building an indigenous orbital intelligence network, Digantara reduces dependence on foreign data providers and strengthens India’s strategic autonomy.

It also positions India as a potential exporter of advanced space surveillance services, fostering international cooperation and transparency in orbital operations.

MOSAIC’s introduction marks a significant milestone in India’s space modernisation. It provides a scalable, AI-driven solution to one of the most pressing challenges of the 21st century: ensuring safety, security, and sustainability in an increasingly congested orbital environment.

Agencies