Build, Manage, and Deploy Machine Learning

Models with Ease

Getting Started with ML Modernization

ML solutions provides a way to deploy the use cases readily with just a few clicks, making it easier for you to get started. Our solutions are fully customizable and support one-click deployment and fine-tuning of more than 150 popular open-source models, such as natural language processing, object detection, and image classification models.

We offer services such as

ML Integration on Existing AWS Infrastructure

Efficient Data Preprocessing and Training for ML

Simplified Modeling and Model Versioning in ML

Seamless Implementation of Complete ML Pipelines

Effective Model Monitoring and Retraining for ML

Use cases

Anomaly Detection

Identify potential fraud or unusual activities in financial transactions using anomaly detection. 

  •  Utilize machine learning algorithms and statistical analysis to identify deviations from expected patterns. 
  •  Analyze transactional data to establish normal behavior patterns for each customer or account. 
  • Continuously monitor incoming transactions to flag anomalies. 
  • Detect suspiciously large transactions, unusual frequency or timing, and geographically distant transactions. 
  • Trigger automated alerts or notifications upon detecting an anomaly. 
  • Investigate flagged transactions or accounts promptly to mitigate risks. 

Automated Loan Underwriting 


Automate loan underwriting by analyzing borrower data, credit history, and relevant factors. 

  • Streamline approval process, reduce manual work, and improve efficiency. 
  • Increase accuracy and consistency in loan decisions using advanced algorithms. 
  • Define rules and criteria based on risk appetite and regulatory requirements. 
  • Continuously refine and enhance algorithm for improved decision-making accuracy. 

Content Recommendations 

Analyze user viewing history, ratings, and interactions for personalized content recommendations. 

  • Consider factors like genre preferences, similar user behavior, trending content, and contextual relevance. 
  • Generate curated lists of movies, TV shows, and media based on user preferences. 
  • Present recommendations through personalized suggestions, notifications, or in-app suggestions. 
  • Continuously refine recommendations based on user feedback and evolving preferences.


Simplify. Boost. Save.

Simplify Scaling

Effortlessly scale ML in production, handle large datasets with ease, and accelerate model deployment

Boost Productivity

Streamline ML workflows, reduce operational overhead, and empower ML teams for enhanced productivity

Lower Operational Costs

Consolidate and standardize ML platforms, streamline onboarding, and optimize resource allocation for cost savings

Why Choose ACC?

Accelerated Development:

Partnering with ACC can help to accelerate your project development. ACC brings in-depth knowledge of best practices, pre-built ML models, and reusable components using AWS Sagemaker, enables faster implementation and reduces development time and costs. 

Infrastructure and Scalability:

ML projects often require robust infrastructure and scalable resources to train and deploy models efficiently. ACC can help design and implement scalable architectures using AWS services like Amazon Sage Maker, AWS Lambda, and Amazon EMR, ensuring your ML solutions can handle varying workloads and demand. 

Expertise and Guidance:

ACC specializing in ML can offer extensive expertise and guidance throughout the project lifecycle. We have experience working with various ML technologies, frameworks, and AWS services, and can help you choose the right tools and approaches for your specific project requirements. 


Case study

Designing and Implementing an ML Pipeline to Predict ETA for Bus Routes

Accurate Bus ETA Predictions for Improved Services and Efficiency

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