Edge AI

Adapting, optimizing and deploying AI/ML models for heterogeneous edge compute across MCUs, MPUs, DSPs, NPUs, FPGAs and SoCs with performance-efficient model transformations.

Services

Model Engineering & Platform-Aware Optimization

Engineering end-to-end optimization of AI and ML models and runtimes for target processors and platforms to reduce com-pute, memory and power while preserving accuracy, combining model adaptation and hardware-aware optimization including custom development, retraining, pruning, quantization, model surgery and mapping to MCUs, MPUs, NPUs, GPUs and FPGAs.

Application Integration & System Optimization

Designing and integrating end-to-end edge AI applications spanning sensor ingestion, preprocessing, inference, post-processing and data handling across vision, audio,  speech and multimodal use cases, with system-level optimization including runtime tuning, scheduling, memory management  and data movement for low-latency deterministic execution.

We enable enterprises to run AI at the edge by tailoring models for constrained compute through architecture adaptation and acceleration. Core strengths include model optimization, hardware mapping, inference pipeline integration and perfor-mance tuning for low-latency, efficient and reliable edge deployment. 

Core

Capabilities.

Edge AI Platform & Software Ecosystem Partner

Enabling edge AI platforms through SDKs and optimized libraries for AI, deep learning, multimedia and signal processing, with product engineering support across libraries, toolchains, compilers and reference model repositories, working closely with silicon and platform partners to accelerate adoption and reduce time-to-market.

Architecture Modelling & Validation

Designing and validating AI compute architectures across pre- and post-silicon phases using detailed modelling and benchmarking of compute units, memory hierarchies, interconnects and peripherals, enabling SoC designers to optimize efficiency, reduce power consumption and meet application-level performance targets.

Solutions

Vision Intelligence at the Edge 

Edge-based vision solutions spanning classical computer vision, deep vision models, and emerging Vision-Language Models and Vision-Language-Action models, enabling real-time object and people detection, tracking, scene understanding, visual reasoning and action grounding for intelligent devices operating under edge compute, latency and power constraints. 

On-Device Voice and Audio AI 

On-device speech and audio AI supporting keyword spotting, wake-word detection, voice command interfaces, speech-to-text, spoken intent extraction and audio classification, including noise-robust signal proce-ssing and efficient neural inference to enable low-power, low-latency, privacy-preserving human–machine interaction without cloud connectivity. 

Autonomy & Navigation Systems 

Edge AI for autonomous navigation with SLAM, state estimation, obstacle avoidance, trajectory planning and behaviour models, deployed alongside  perception and control loops to enable real-time decision-making and safe operation of robots, drones and AMRs in dynamic, resource-constrained environments with strict latency and reliability requirements. 

Motor Control, Monitoring & Predictive Analytics 

Edge AI solutions combining signal processing and machine learning for real-time control, condition monitoring, anomaly detection and predictive maintenance, covering motor intelligence, vibration and current analysis and closed-loop optimization for appliances, HVAC, robotics and industrial equipment with deterministic timing guarantees. 

Accelerators 

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VeSLAM

VeSLAM is a comprehensive SLAM algorithm suite built using Lidar and Visual sensors meant for broad range of environments and use cases. This is a customizable accelerator IP which can be tailor made for indoor environments such as home, office, factory environments and outdoor environments such as agricultural, defence and port/logistics. 

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