We quickly built a few prototypes with RAG, we needed the models to perform well consistently and reliably.We needed help making them production ready.
We built a few chatbots with LLMs, we needed help navigating the AIML world to identify and build a truly impactful solution for our business.
We needed specialized talent, a team of experts with ability to convert published research into a product, highly trained experts in deep neural networks and AI architectures.
We needed hands on experts that understand models, training, finetuning, and pipelines to the nuts and bolts for building our solution.
We needed a a full stack AI team with skill set across Data Engineering, Data Science, MLDevSecOps, DNNs, and Machine Learning.
We were building an internal machine learning and AI team, we needed help setting up our platform, process and organization design to create a productive team.
We needed an entire team of experts that can scale our organization quickly and add velocity to our deliveries, hit the ground running.
Security, Governance, Quality of results, Performance, Scalability, Query Cost Optimization and Mature pipeline development needed deep expertise in AI Architecture.
We needed a team with expertise in Quant Finance and Machine Learning.
Their Models gave us an advanced start, their back end system management team saved us a lot of money.
We were layering Agents on top of our ERP workflows, needed a team with deep knowledge on Agentic AI and specialized expertise in multiple ERP packages.
We define, design, build, deploy, manage and rapidly evolve enterprise quality MLAI solutions that add value and velocity to your business.

Extensive image-based feature engineering identified key aspects distinguishing morphed fake brand images from worn-out real logos.
Extensive work in image pre-processing and creation of a Chroma vector DB for Brand and Brand related metadata.
Made Architecture reviews and compliance self service adding velocity to the deployment of over 140000 applications.
Built and tuned a deep network (4 hidden layers) fixed income instrument pricing, used Yahoo Finance Data set for training and tuning the network.
Implemented Many to Many Matching Algorithm by extending Gale-Shapley in R.
Built numerous analytics models in Java, C++, Matlab, R for options, and derivatives.