NayanLabs.ai integrates heterogeneous sensor modalities into a unified, low-latency fusion pipeline — purpose-built for IoT, wearables, defence, industrial, and autonomous applications.
Heterogeneous sensors speak different languages — different timebases,
noise profiles, coordinate frames, and failure modes. NayanLabs.ai provides
the middleware and co-design expertise to unify them into a single,
calibrated, low-latency world model.
From a single-sensor node to a full multimodal stack, we handle
time-alignment, cross-modal calibration, dropout resilience, and
edge-optimised inference — so your team can focus on the application.
Hardware-level timestamping and software interpolation across sensors with mismatched sample rates.
Intrinsic, extrinsic, and cross-modal calibration pipelines. Automated and field-updateable.
Probabilistic and learned fusion. Robust to individual sensor dropout, degradation, or occlusion.
Quantised, hardware-optimised models with deterministic latency and defined power envelopes.
Each integration ships with calibration tooling, driver support, and fusion primitives — validated on real hardware across our reference deployment environments.
Industrial arms, humanoid platforms, and warehouse AMRs demand sensor fusion that survives vibration, occlusion, and dynamic environments without cloud dependency.
AMRs, UAV stacks, and full AV pipelines — multimodal fusion at the edge with the safety margins required for real-world deployment.
SWAP-constrained sensing for contested environments. Resilient fusion across denied-GPS and RF-degraded scenarios with safety-critical integrity guarantees.
Factory floor, medical devices, and heavy machinery — predictive sensing with deterministic real-time guarantees and IEC 61508 awareness.
SoC + sensor + power co-design for always-on edge inference. Milliwatt budgets. Continuous biometric and context awareness without cloud round-trips.
Cross-modal fusion across vision, event cameras, ToF, LiDAR, radar, IMU, and biometric sensors. Time-aligned, calibrated, and probabilistically consistent in real time.
Sensor-near compute with analog/mixed-signal AI efficiency. Quantisation-aware pipelines, latency budgeting, and real-time inference constraints baked in from day one.
Constraints-aware ML that treats power, accuracy, and latency as joint optimisation variables. Closed-loop sensing–inference–control with failure mode analysis for production deployment.
Heterogeneous sensor streams — vision, radar, IMU, ToF, audio, biometric — hardware time-aligned at ingestion.
Automated intrinsic and extrinsic calibration. Cross-modal spatial and temporal registration. Field-updateable.
Probabilistic and learned fusion yields a unified world state, robust to individual sensor dropout or degradation.
Quantised, hardware-optimised models deliver deterministic latency within the defined power envelope.
Continuous in-field calibration, drift correction, and model updates sustain performance over the product lifecycle.
The gap between a proof-of-concept sensor node and a production-grade fusion system is calibration, robustness, and power — not the algorithm. NayanLabs.ai closes that gap with validated fusion middleware co-designed with the silicon constraints that real-world edge deployment demands.
Whether you are integrating a novel sensor modality, hardening a defence perception stack, or bringing a wearable product to market — NayanLabs.ai can accelerate your path to a production-grade fusion system. Reach out for a technical briefing or partnership discussion.
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Thank you — our team will be in touch within 2 business days. In the meantime, feel free to explore our sensor coverage and capabilities above.