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
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
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.

VeSoniq is a low power wake word and command detection solution built for always on IoT devices. It supports multiple wake words and up to 30 commands, allows custom wake words with minimal training data, offers local language support for global markets and provides speaker specific customization for added security.

VeSpot is a lightweight Visual AI model for real time object detection on MCUs, MPUs and NPUs, delivering up to 9x higher compute efficiency with 35 percent fewer parameters and a 32 percent smaller model size than YOLOv11n, enabling fast, accurate and cost-effective deployment across robotics, visual inspection, surveillance and industrial automation.