Automation Anywhere Aisera Solutions - 2026 Pricing, Features, Reviews & Alternatives

Aisera is a cloud-native SaaS and on-premises agentic AI platform built for Global 2000 and mid-market enterprises. It deploys a coordinated system of AI agents and assistants that autonomously handle decision-making, process orchestration, and task execution at scale across IT, HR, Finance, Customer Service, Facilities, and Operations functions. The platform combines conversational AI, AI-powered search, AIOps, and self-service resolution capabilities, integrating with over 100 enterprise applications including ServiceNow, Salesforce, Workday, Zendesk, Oracle, Atlassian, BMC, and Microsoft 365. It serves organizations across financial services, healthcare, retail and e-commerce, telecom and utilities, media and entertainment, and transportation and logistics.

Core capabilities include out-of-the-box and custom AI agents built via Agent Composer using natural language, an Enterprise AI Copilot with federated search and domain-specific large language models (LLMs), and Agent Assist with triage, summarization, answer generation, and next best action recommendations. Workflow automation is delivered through AI Workflow Studio, Event Studio, Hyperflow Studio, and Prompt Studio, all supporting low-code and no-code configuration. Conversational AI 2.0 handles intent matching, contextual disambiguation, multi-intent queries, and context switching, while Retrieval-Augmented Generation (RAG) powers accurate knowledge retrieval across enterprise repositories. Multilingual support spans over 100 languages with built-in language detection. The Aisera Unify backbone adheres to open standards (A2A, MCP, AGNTCY) for multi-agent ecosystem interoperability, and the TRAPS Framework governs trusted, responsible, auditable, private, and secure AI deployment.

AIOps capabilities deliver proactive incident detection, automated root-cause analysis, noise suppression, spatiotemporal correlation, and full-stack observability, with OpenTelemetry integration within the LLM gateway for agent-level observability. LLM Studio supports tailored model tuning using organizational knowledge and ITSM data, and the platform accommodates buy, build, or bring-your-own LLM configurations, including on-premises LLM models for data privacy requirements. Automated machine learning and reinforcement learning models are trained on 150 million tickets and over 1.1 billion conversations. Additional capabilities include Ticket Concierge for proactive ticket resolution, Campaigns for broadcast messaging across MS Teams, Slack, and other channels, scheduled automation triggers, event-based workflow execution, sentiment analysis, churn prediction, and predictive analytics for financial performance and budget anomaly detection.