DIGITAL TECH - Pi-technologies

Get to know Reality

Extended Reality (XR) is an umbrella term for all the immersive technologies. The ones we already have today Augmented Reality (AR), Virtual Reality (VR) and Mixed Reality (MR), plus those that are still to be created. They are used in entertainment, military training, engineering design, robotics, manufacturing and other industries. via smartphones, tablets, heads-up displays, or VR glasses.

AR overlays digital content and information onto the physical world as if they’re actually there with you, in your own space. The goal is to create a system in which the user cannot tell the difference between the real world and the virtual augmentation of it.

VR is the use of computer technology to create a simulated, artificial environment that places the user inside an experience using VR glasses.

MR bridge the digital and physical worlds where the virtual objects placed in the real world can be interacted with and respond as if they were real objects. A user can navigate this environment and interact with both real and virtual objects.

AUGMENTED, VIRTUAL, MIXED

Extended Reality

Get to know Reality

VR is the use of computer technology to create a simulated, artificial environment that places the user inside an experience using VR glasses.

Solutions

Artificial Intelligence

Data pipeline , data ingestion, data transformation (ETL), and data modelling.

Agile/SCRUM enterprise-scale software development

Patch-processing and tools ( Nifi, Midpoint, MapReduce, Yarn, Pig, Hive, HDFS)

Restful web services ,code development, deployment, versioning, and build tools (Eclipse, git, svn, Jenkins)

Distributed framework as a full-stack auto-tuning infrastructure across the application/algorithm, operators, and compiler Kubernetes, Docker, Kubeflow.

Stream-processing ( Kafka, RabbitMQ, Storm, etc.)

Applications NoSQL stores (eg, ElasticSearch, Hbase, Cassandra, MongoDB, CouchDB, DyanamoDB)

Cloud architecture with AWS EC2, Amazon Kinesis, S3, VPC, Elastic Search.

GPU computing (CUDA, OpenCL) and HPC (MPI, OpenMP)

Machine Learning and Deep Learning model development using frameworks such as Caffe2, Tensorflow, Tensorflow-Lite, Keras, ONNX, PyTorch, Theano, MATLAB.

Systems-level performance modelling, profiling, and analysis.

High performance image processing algorithms on state-of-the-art processing architectures.

Embedded systems messaging protocols such as UART, SPI, I2C, CAN BUS, TCP/IP, etc.

Technical advising in image processing and application software.

Multi-media SDK DeepStream, Gstreamer, Nvidia Clara Toolkit.

Development of cross-platform software that uses hardware-accelerated libraries for multimedia, graphics and display.

Products for time-series analysis for the Banking and Finance domain.