payroll management system

Infusing Enterprise Application with AI/ML

Moving from Passive to Active ERP

ERP applications traditionally do as dictated. It absorbs tons of data every time a business transaction takes place – from customer order to RFQs, purchase request to invoice, travel expenses to reimbursement claims. But the data is never wielded to the advantage of the employee or the employer.

The solution lies in enterprise application becoming active, instead of remaining passive. At Ramco, our ERP software is integrated with Artificial Intelligence (AI) and Machine Learning (ML) which can analyze the data, question a user, and recommend optimum solutions to implement. It is made for the future where the applications should be able to think, predict and prompt. The potent combination of AI and ML can improve productivity, simplify complex transactions, make data accessible anytime and anywhere and transform technology from being a mere support tool to that which can drive digital transformation!

Infusing AI & ML into Enterprise Applications

Universal validation & defaulting

Prompting the right choices based on past trends, to help you select the best of solutions

Preventing damage

 Recognizing errors that can be rectified; helping you prevent damage and even fraud attempts

Cost and resource saving

 Saving money & resources for the organization through error-free data inputs, optimal data capture et al


  Predicting failures through AI powered forecasting, helping the organisation take better functional and strategic decisions

Accelerating Growth

Artificial Intelligence and Machine Learning can accelerate business development, garner growth opportunities and lay down the roadmap for achieving future goals as well. With machine learning sharpening AI skill sets and AI delivering cognitive and intellectual capabilities to machine, this technology duo can work magic in terms of deploying meaningful solutions across the enterprise landscape.

Reduction of data entry

Leveraging behavioural analysis and prediction, and using machine learning to reduce data entry to its bare minimum

Automate tasks

Utilizing data patterns intelligently and taking into record historical trends and data, to automate routine tasks

Streamline processes

Its ability to act cognitively and swiftly can help in streamlining internal processes and tasks, thus improving efficiency

Nimble technology

The technology can quickly adapt itself to changing market dynamics, and can be intelligent enough to even anticipate forthcoming events

Reliable architecture

ML Platform uses microservices architecture, containing several intricate components, that support quick and reliable delivery of complex applications

High capacity AI Platform

It enables learning, interpretation and application as well, and is supported by an API Gateway which handles all the security between the servers

Driving Smart Disruption

Explore various use cases developed by Ramco that are already being used by some of the leading Fortune 500s and international MNCs. Some of them include for:

  • Ramco CHIA, the AI driven bots, with its engaging, conversational, and trustworthy interface has become the HR bot buddy for 100,000+ users
  • Ramco’s Net Pay Anomaly Detector powered by ML can analyze historical data spanning across years in a fraction of time to spot payroll anomalies
  • Machine learning can help in studying the traits and characteristics that best performers within an organization display which can be categorized and studied so that their potential can be best utilized in relevant areas
  • Aviation bots support efficient part management by maintaining an accurate part inventory, auto-triggering purchase orders, selecting the ideal vendor, and promptly handling AOG situations
  • Predictive maintenance uses AI and ML, specifically for unscheduled events wherein the system can examine data to predict and also continuously learn based on such unscheduled events to refine the prediction
  • Discrepancy Reporting intelligently predicts common discrepancies occurring in aircrafts and machinery, simultaneously suggesting corrective actions as well to fix them
  • Logistics bots enable frictionless computing by proactively delivering information about consignment status among other details
  • Machine learning supports in-memory optimization and last-mile planning that assesses multiple real-time data before delivering the final fleet plan suggestions, including driver and vehicle availability, nature of the consignment etc., simplifying the dreaded task of freight planning

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