Our Portfolio
We define, design, build, deploy, manage and rapidly evolve enterprise quality MLAI solutions that add value and velocity to your business.
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Brand Theft Mitigation
Technologies: Anthropic API, Google API, OpenAI API, Python, Azure, CockroachDB, Airflow.
- Image based feature engineering effort was extensive to identify the aspects of an image that will differentiate between a morphed image of a fake brand and a worn out logo on a physical product.
- Our customized anomaly detection AI network accurately identifies a fake product.
- We built and tuned a subsystem to generate synthetic data for simulating possible genuine logo damage.
Retail Beverage Brand Mix
Technologies: OpenAI API, AzureML, Google VisionAPI, AWS, CockroachDB, Airflow.
- Extensive work in image pre-processing and creation of a Chroma vector DB for Brand and Brand related metadata.
- Object identification, brand identification, OCR price reading, package size recognition problems were solved to make this a successful solution.
- BevAnalytics saved more than 60% of their core operational cost in data collection.
Software Architecture Review
Technologies: OpenAI API, AzureML, OLlama Local Install, AWS, MySQL, Python,AirFlow.
- Made Architecture reviews and compliance self service adding velocity to the deployment of over 140000 applications.
- Architecture review documents and their inputs were used to create a Chroma vector DB of Architecture reviews.
- Used Llama Tiny as the base for fine tuning using Hugging face transformers.
Deep Bayesian Neural Network
Technologies: R, Matlab, Kettle, C++, Java.
- Built and tuned a deep network (4 hidden layers) fixed income instrument pricing, used Yahoo Finance Data set for training and tuning the network.
- Extensive experimentation with features (duration, convexity, vega etc.,) and network depth (all the way to 32 layers).
- Results of Monte Carlo simulations used in training multilayer perceptron (MLP) networks with backpropagation, compared with radial basis function (RBF) network.
Gale-Shapley Matching
Technologies: R, AzureML, Azure, Azure Storage, C#, ASP.NET, BootStrap, Angular, JQuery, TFS, SQLServer, SSRS, SSAS.
- Implemented Many to Many Matching Algorithm by extending Gale-Shapley in R.
- The platform is an extensible HIPAA compliant data collection platform for families that are interested in adoption.the platform has a workflow component that integrated various steps of adoption across many organizations.
- Setup a continuous delivery automation on Azure.
Quant Models for Trading
Technologies: R, Matlab, Kettle, C++, Linux/Unix, C#, SqlServer, Cplex, kdb+, LIM, HDF, JQuantLib, Python.
- Built numerous analytics models in Java, C++, Matlab, R for options, and derivatives.
- Macro alpha strategy based on currency market. (2011 – present). Macro alpha strategy based on ES/GC (2010 -2011)
- Quant2Xchange: Developed a high speed interface between Matlab/R and Fix Engines (TT Fix Adapter) in Java.
