Multiverse Computing helps defense ministries, prime contractors, R&D agencies and aerospace innovators deploy efficient, secure and sovereign AI. As an AI Solutions & Models provider with deep expertise in efficiency and security, we design mission-ready models that fit where they didn't fit before: at the tactical edge, on classified networks and under the strictest operational constraints.
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Run advanced AI on-premises and at the edge, with full control of data, models and inference and no exposure to external clouds.
Bring AI close to the sensor and the decision-maker, with real-time inference that holds up under degraded, jammed or contested communications.
Lower compute, memory and energy requirements unlock more autonomy on battery-powered platforms and more onboard AI capacity per device.
Deploy AI on private, hybrid or air-gapped infrastructure, with full data residency and clean integration with classified networks.
Prepare national security for the post-quantum era with dedicated quantum and quantum-inspired tools for cryptanalysis, PQC migration and secure communications.
Multiverse Computing delivered real-time object detection over more than 670,000 km² of high-resolution, multi-spectral satellite imagery. The optimized model is 80% smaller with no accuracy loss, 43% lower inference latency and 55% lower power consumption, enabling scalable, high-frequency satellite processing at the edge.
Multiverse Computing compressed and optimized a state-of-the-art segmentation and tracking model for onboard deployment on defense-grade processors. The drone makes decisions locally and the operator console receives only events and actionable highlights, preserving resilience under degraded or contested communications.
Multiverse Computing applied progressive compression and quantization to fit a compact detection model into dedicated FPGA memory. Two compression profiles were delivered: a soft profile preserving near-original accuracy and a strong profile maximizing memory and power savings, enabling real-time ship detection fully on-device.
Multiverse Computing delivered a custom quantum cryptanalysis software tool implementing state-of-the-art quantum algorithms, including Shor and Grover, fully tailored to the operational environment. The system was delivered under strict confidentiality with long-term support and a multi-year guarantee aligned with national security standards.
Multiverse Computing delivered a compressed, quantum-inspired optimized version of a 72B-parameter multimodal Vision-Language Model for real-time deployment on edge robotic systems. The model enables on-edge multimodal reasoning and is ready for secure fine-tuning with private defense data.
Multiverse Computing built a radar signal detection model that trains 100x faster and uses 100x fewer parameters than state-of-the-art benchmarks. The model holds 95 to 99% accuracy even at high noise levels and outperforms benchmarks across all signal-to-noise ratios (patent pending).
Multiverse Computing delivered a sovereign, on-premises object detection model through a five-phase pipeline of profiling, training, compression, healing and validation. The result delivers 45% parameter reduction and 20% lower computational load while preserving detection accuracy, deployable on defense-grade edge GPU hardware via ONNX and TensorRT.
Multiverse Computing designed a multi-sensor maritime surveillance capability combining advanced detection, anomaly detection, a Complex Event Processing engine and explainability layers. The pipeline is delivered as a containerized AI service ready for integration into the client's existing naval surveillance platform.
Multiverse Computing developed a custom computer vision pipeline trained on a purpose-built dataset of more than 11,000 manually labelled images, optimized for in-cockpit deployment. The system achieves 90% accuracy on the initial gesture set with real-time inference ready for integration into cockpit hardware.
Missiles, autonomous vehicles and high-speed platforms operating in contested or jammed environments require navigation and trajectory correction without reliable GNSS signals.
Compressed visual and inertial navigation models combining terrain matching, on-board image correlation and sensor fusion, designed to run inside platforms with severe constraints on power, space and thermal dissipation.
Defense logistics involve complex, multi-echelon supply chains with strict reliability, traceability and availability requirements across distributed bases and theatres.
AI-driven optimization combining forecasting, routing and inventory models with quantum-inspired algorithms to plan, allocate and resupply across constrained logistics networks.
Aircraft, vehicles, vessels and ground systems generate vast amounts of telemetry, yet unplanned failures still drive downtime and operational risk.
Predictive maintenance AI based on sensor fusion, time-series modelling and compressed models deployable on the platform itself, with secure, on-premises inference.
The proliferation of small UAS creates a constant detection, classification and response challenge across critical sites, borders and tactical theatres.
Compact computer vision, RF signal and multi-sensor fusion models deployable on edge hardware, designed to detect, classify and track unauthorized UAS in real time.
Defense and intelligence teams need to analyse massive volumes of open-source content across many languages and formats to surface signals relevant to national security.
Compressed multilingual language models combined with classical and quantum-inspired retrieval, entity extraction and pattern detection, deployable on sovereign infrastructure.
Modern multi-domain operations require integrating intelligence, logistics, communications and platform data into clear, actionable decisions under tight time constraints.
Decision-support AI combining forecasting, simulation, optimization and natural language interfaces, available as compressed models that can run on classified networks.
Realistic training and wargaming require high-fidelity simulations, intelligent synthetic actors and the capacity to scale exercises across distributed environments.
AI-powered synthetic agents and environment models built on compressed language and vision models, capable of running in classified, on-premises simulation infrastructure.
Defense organizations manage huge volumes of classified documents, reports and intelligence products that need to be processed, indexed and exploited without compromising security.
Sovereign, on-premises Multiverse Computing language models for classification, summarization, search and translation of sensitive documents, deployable on air-gapped infrastructure.
In contested or remote environments, medical teams must perform triage with limited resources and rapidly evolving situations, often without reliable connectivity.
Compressed multimodal AI models combining vision, biosignal and language inputs, deployable on portable devices for assisted triage and decision support in field conditions.
Multiverse Computing helps defense innovators build AI capabilities that are faster, smaller, more secure and ready for the operational reality of modern missions. Talk to our team about deploying advanced AI on your platforms, in your infrastructure and under your security requirements.
