Digital Assets Management Solutions delivers a single, unified system, software and interface for automating an enterprise's IT infrastructure, applications, and processes that includes monitoring, event handling, ticketing and remediation. DAMS bases its actions on business rules from deep domain knowledge, guided machine learning and artificial intelligence to take precise and intelligent actions to keep the businesses running at peak performance.
The IT managed services market is getting disrupted from two angles. Digital agendas are pushing customers to move more and more to the cloud and most recently, to the public cloud. This changes the expectations of the managed services providers. The second big disruption is the wave of automation. While IT service providers have talked about automation forever, not much progress has been made in this space. Primarily because the business model was based on labour arbitrage. But now, customers are demanding more automation and are looking for fresh solutions from new players that can really accelerate their adoption of cloud and also bring in AI and machine learning to automate everything in the L1 service desk and slowly move up the chain into L2 and L3 services as well. DAMS is positioned to take on this new requirement from customers. We are disrupting the managed services market by bringing in the intelligent automation.
Automated management for applications and infrastructure, with automated monitoring, incident management and problem management
Platform built on intelligent automation with customisable levels of automation
Executive, multi-level, multi-cloud dashboards
100+ ready-to-deploy automation templates for common recurring incidents
Integration with ITSM tools for complete lifecycle automation
Ticket enrichment and prioritisation for problem tickets
Multi-channel support through AI chatbots, email, IVR, SMS, etc.
DAMS is built on the cloud platform and natively supports a multi-cloud environment. It leverages technologies like machine learning and AI to minimise the human intervention in terms of monitoring, event handling, ticketing and remediation. By using reinforced learning methods, it slowly improves the accuracy of automated fixes as and when the issues arise. It's built in continuous learning system creates virtual models of the infrastructure using live data and offers predictive and prescriptive solutions.