Containerized Python model-serving stack for specialized vision/NLP handlers such as MICR, signature, and verbiage detection.

AI Inference, Containerization, Model Serving

Duration

1 Year

Year

2024

Region

USA

Model serving packages reusable serving components (MS Handlers, MScommons, Common Except) with deployment tooling and runtime configs for production inference.

It supports domain-specific handlers and tokenizer/model resources, enabling standardized serving of trained models in controlled environments.

Problems

Deploying multiple model handlers consistently across environments was complex.

Opportunities

Create a unified container-friendly serving runtime for AI model handlers.

Solutions

Built modular serving packages, shared commons, deployment scripts, and runtime configuration for inference endpoints.

Future Trends

Unified model registry integration and A/B rollout strategies for model handlers.

Our Projects

AI Fraud Engine

End-to-end fraud analytics platform for training, evaluating, and serving transaction fraud predictions in online and offline modes.

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NLP Web Service

Django REST web service for call-quality evaluation and historical evaluation retrieval using NLP engine integrations.

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NLP Processing Framework

Modular NLP framework covering preprocessing, feature engineering, and vectorization for conversation and text analytics.

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Model Serving Platform

Containerized Python model-serving stack for specialized vision/NLP handlers such as MICR, signature, and verbiage detection.

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Model Inference Service

Real-time inference API service for invoking deployed AI models with resilient, enterprise-ready request handling.

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Financial Verification Suite (FVS)

AI-powered computer vision platform for check/image verification including signature, MICR, amount, date, and verbiage analysis.

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Successful Project Deliveries

Highlighting some of our most impactful and innovative solutions

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