Artificial Intelligence. For humans. By humans.

The bots are coming; well - they aren't just on the way; they are already among us. Leverage the power of machine-driven cognitive analysis to derive insights relevant to your industry. Be it image, video, audio, speech, text or an aggregration of data types, we have developed proven techniques that can extract actionable intelligence.

Beyond the hype - AI by Ignitarium.

Analytics : Expertise

Data Management

Data quality is crucial in artificial intelligence because it directly impacts the performance, accuracy, and reliability of AI models.

Our team has expertise in

Preprocessing data from various 2D and 3D sensors – camera, LiDAR and Radar

Synthetic data generation

Virtual sensors – using stored sensor data

Automated data labeling

Utilities for parameterized audio and video test stream generation

Data versioning

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Model Development

Expertise in developing power and memory efficient Deep Learning (DL) based solutions using Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Transformers and Generative AI algorithms

Expertise in developing classical machine learning algorithms such as Support Vector Machines (SVM), dimensionality reduction techniques, Markov models for solving classification, regression, and time-series forecasting problems

We have capabilities to port AI models to all kind of edge devices and cloud platforms

Model customization and graph surgeries to address layer support on different types of AI accelerators

Model pruning and optimization to enhance the model runtime performance

Benchmarking – competitive benchmarking, power vs performance benchmarking and accuracy benchmarking

Click to view the MLMark white paper.


We partner with AI chip companies who are in the process of developing AI hardware and software SDKs, and help reduce time-to-market for AI accelerators.

With our deep understanding of the customer’s hardware architecture, memory constraints, computational operations, our team can support:

AI SDK kernel library development, enhancement, and porting

Custom operator development and optimization for DL accelerators

Full graph, sub graph porting and optimization

DSP library porting and optimization

Developing and optimizing OpenVX kernels, GStreamer plugins

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Architect, design and develop AI applications for various use cases across industries

Application development on Edge devices and on cloud platforms

With expertise in Embedded, AI, web development and cloud, we can develop complete solutions integrating device, cloud and user inputs

Validation of algorithms, models and applications

Use Cases

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Predictive Battery Analytics

Battery Analytics provides vital statistics of the battery which can be used to calculate or predict the State of Charge (SOC), State of Health (SOH) and Remaining Useful Life (RUL).

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Autonomous Mobility

Autonomous mobility is enabled by sensor fusion algorithms - which fuse multiple sensors (camera and LiDAR) using both classical & deep learning approaches, and navigation stacks.

Medical Imaging

The diagnostic accuracy and efficiency of medical imaging is being enhanced through advanced image analysis and pattern recognition algorithms, and also by automated patient positioning during scans.

Defect Detection

Ignitarium's visual AI based defect detection platform, TYQ-i, captures visual data and uses AI models to detect defects in civil infrastructural assets like rail tracks and wind turbines.

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Advanced Robotic Picking

Advanced robotics picking is revolutionizing industries by using cutting-edge technology to automate the precise and efficient retrieval of various objects, streamlining production and logistics processes.

Factory Worker Analytics

Factory Worker Analytics includes person and personnel protective equipment (PPE) detection such as helmet, jacket and goggles to optimize workforce productivity and safety. It is in-field trainable for new artifacts.

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People Flow Tracking

People & object analytics in indoor and outdoor environments includes Counting and tracking, Flow monitoring, Dwell timing and Heat maps using 3D LiDAR and deep learning.

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Surveillance in retail, employs aisle monitoring, shopper gaze detection, suspicious activity detection to analyze shopping patterns, optimize store layout and prevent theft.

AI : Platforms, Libraries & Frameworks

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Case Studies