Driving Autonomous IT withignioâ„¢ AI Agents
ignio’s AI agents, with their ability to perceive, reason, act, and learn deliver measurable business value and transform IT operations.​
Powering AIOps with Agentic orchestration
A network of specialized agents, which autonomously drives AIOps lifecycles​
AI Agents
for the autonomous enterprise
Event Management
Reduces alert noise and generates timely, relevant alerts for improved focus ​and efficiency​.
Incident Resolution
Automatically diagnoses and resolves incidents for faster issue resolution​.
Cloud Cost Optimization
Understands and quantifies cloud usage, costs, and business value, while optimizing for efficiency and savings​.
Proactive Problem Management
Eliminates or prevents recurring issues by leveraging insights from current analysis to drive proactive solutions​.
Business SLA
Predictions​
Predicts future behavior and provides early warnings of potential SLA violations.​
Empowering AIOps with an agentic AI platform​
Digitate’s Agentic AI platform can orchestrate multiple AI agents to get work done and boost productivity with minimal human intervention. ​
- Reduced downtime by proactive issue resolution
- Increased efficiency by autonomous decision making
- Improved resilience by automated incident resolution
- Improved stability by proactive problem management​
How Digitate's AI Agents work​
Digitate enables various AIOps use cases through the agentic orchestration of 6 key types of agents
Perception
- Interprets context
Description
Uses context mining and text mining, NLP, LLMs, and data mining to extract insights, identify trends, and establish normal behavior.​
Reasoning
- Reasons and makes decisions
Description
Applies AI/ML techniques, memory, and varying levels of complexity to translate statistical observations into domain-aware insights and recommendations.
Action
- Executes actions
Description
Ranges from simple static rule-based agents that automate tasks, to complex dynamic context-driven agents that automate situations. ​
Learning
- Continuously learns from interactions
Description
Learns from data, system responses, human feedback, and GenAI-powered conversational intelligence to interact with users and SMEs.​
Internal control
- Can ensure fairness, trustworthiness, conformance
Description
Deploys responsible AI practices and guardrails, and action-firewall to ensure safety and conformance. ​
Augmentation
- Can enable human-agentic interfaces
Description
Leverages collaborative learning, conversational intelligence, GenAI for intuitive experiences, and learning from human experts through LLM-powered interfaces.  ​
Resources and insights
Frequently asked questions
What is Agentic AI?
Agentic AI is an artificial intelligence system that can accomplish a specific goal with limited supervision. It consists of AI agents—machine learning models that mimic human decision-making to solve problems in real time. In a multiagent system, each agent performs a specific subtask required to reach the goal and their efforts are coordinated through AI orchestration​
What are agents?
Agents are software systems that perform specific tasks. ​
What are AI agents?
In the context of AI, AI agents are systems that use AI to perform specific tasks. These tasks could be of different types such as reasoning, decision making, etc.​
What is the difference between AI agents and Agentic AI?
AI agents are developed to perform specific tasks. ​
Agentic AI orchestrates multiple AI agents to autonomously achieve specific goals.​
