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 compute, memory, and power while preserving accuracy. This combines model adaptation with 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. This includes system-level optimization such as 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 performance 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 through detailed modelling and benchmarking of compute units, memory hierarchies, interconnects, and peripherals. This enables 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 processing and efficient neural inference to enable low-power, low-latency, and 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
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.
