Syent embeds adaptive, multi-modal sensor fusion directly into constrained microcontroller environments — enabling decentralized AI decisions at the very edge of physical systems.
We've rearchitected the inference pipeline from silicon up — replacing brute-force compute with distributed, event-driven signal processing tightly coupled to sensor inputs. The result: on-device intelligence that fits within the energy and memory envelope of standard microcontrollers.
Unified signal aggregation across heterogeneous sensor types — temporal, spatial, thermal, acoustic — processed asynchronously within a single constrained compute context.
Federated inference across node clusters — no central orchestrator required. Each endpoint retains full decision capacity while contributing to a coherent system-level model state.
Activity-driven execution eliminates idle power waste. Compute resources activate only in response to meaningful signal events, maintaining sub-milliwatt standby profiles.
Dynamic model quantization adjusted at runtime to fit the live memory footprint — enabling deployment across the full MCU hardware spectrum without firmware rebundling.
Local model adaptation in response to operational drift — no data exfiltration, no retraining cycles. The system recalibrates in-place as the physical environment evolves.
Precise time-indexed event streams map physical transients to compact representations — preserving causal structure across distributed nodes without synchronization overhead.
Raw analog and digital streams are normalized and time-aligned across heterogeneous modalities before reaching the inference layer — eliminating pre-processing overhead at the application level.
A sparse, event-driven compute architecture executes inference within the memory and power envelope of commodity MCUs. No external accelerator. No cloud offload.
Peer-to-peer model state synchronization across node clusters — gossip-based protocols ensure system-level coherence without a central coordinator or network dependency.
Operational intelligence without cloud infrastructure — across the domains where latency, privacy, and power constraints make centralized AI architecturally unsound.
Continuous multi-axis sensor fusion across rotating machinery, thermal arrays, and vibration inputs — inferring degradation state locally without PLC-to-cloud roundtrips.
Decentralized perceptual inference across vehicle subsystems — sensor signals fused and acted upon at the node level, preserving real-time guarantees even when network links are unavailable.
Distributed edge AI across smart building, utility, and civil infrastructure networks — adaptive anomaly detection with zero data egress and multi-year battery operation.
Always-on biosignal processing on resource-constrained wearable hardware — fusing multimodal physiological inputs with sub-milliwatt draw and fully on-device pattern recognition.
Syent's platform is designed against production hardware limits — not lab benchmarks. Every parameter reflects what ships.
Request DatasheetWe work directly with engineering teams to deploy Syent's edge AI fabric
within existing MCU hardware. No new silicon required.
Currently accepting design partners in industrial, defence, and med tech verticals.