What is Aisera?
Aisera is an agentic AI platform for enterprises, offering a unified, scalable AI agent system that supports both out-of-the-box functionality and custom AI agent development. Through Agent Composer, the platform enables users to create agents via natural language, leveraging open standards like A2A, MCP, and AGNTCY to achieve cross-application and cross-tool integration. Additionally, it includes a built-in LLM gateway and OpenTelemetry observability capabilities, ensuring reliable execution and ongoing optimization.
Key features
It supports natural-language-driven AI agent construction (Agent Composer), enabling users to create domain-specific agents for scenarios like IT, HR, and procurement—without any coding required.
The platform features cross-domain autonomous execution capabilities, such as automatically managing employee account access, distributing software, resolving tickets, triggering procurement based on inventory alerts, handling invoices throughout their entire lifecycle, and tracking orders in real time—among other complex tasks.
Use cases and audience
It is tailored for enterprise users across functional departments including IT, HR, customer service, finance, procurement, compliance, and healthcare, making it ideal for medium- to large-sized organizations that require cross-domain collaboration, eliminate data silos, and enable autonomous execution with continuous learning.
- IT support automation: Automatically handles requests such as employee password resets, VPN access, and software configuration, supporting multi-channel access via Microsoft Teams, email, and web portals.
- Self-Service HR: Reengineer the employee onboarding process, automate the management of leave requests, approvals, and tracking, as well as the querying and updating of benefits and insurance information.
- Intelligent Customer Service Response: Automatically resolve common issues—such as connectivity problems, billing inquiries, or upgrade requests—via IVR, chat, SMS, and web-based virtual agents, reducing inbound call volumes and improving first-call resolution rates.
User requests in natural language—such as password resets, leave requests, or order inquiries—alongside ITSM data, organizational knowledge bases, historical tickets and expert feedback, and real-time business metrics (like inventory levels or invoice data).
Automated execution outcomes—including account recovery, software activation, and ticket closure—plus generated knowledge entries and automated scripts, real-time alerts (such as inventory warnings or compliance anomalies), and personalized search results filtered according to user permissions.
Frequently asked questions
Does Aisera support enterprises’ own large-scale models?
Support: Customers can use the proprietary large model Aisera, or integrate their own large models, and leverage LLM Studio to customize and fine-tune them using organizational knowledge and ITSM data.
How does Aisera ensure the reliability and transparency of AI agent execution processes?
Continuously evaluate agent performance through built-in test suites, and rely on OpenTelemetry integration to achieve LLM gateway-level observability, ensuring reliability, transparency, and operational excellence.
How to use
- 01
Select an appropriate agent from the pre-built AI Agent library, or create custom agents using natural language through Agent Composer.
- 02
Integrate existing enterprise applications, tools, and systems via Aisera Unify, building a unified ecosystem based on A2A, MCP, and AGNTCY open standards.
- 03
Deploy Aisera Assistant and Agent Assist to enable cross-domain execution of complex operations.
- 04
Continuously evaluate agent performance using test suites, and achieve LLM gateway-level observability through OpenTelemetry integration.
Benefits and limitations
Benefits
- Reduce costs through automation
- Boost productivity with AI-powered assistance
- Faster resolution times enhance customer satisfaction
- Provide a unified platform for various business functions
- Offer real-time analytics and reporting
Limitations
- Implementation may require an initial investment
- Reliance on AI may reduce human interaction
- Requires proper training and configuration to achieve optimal performance
- There may be security risks when handling sensitive data.
Official website & sources
Updated on 2026-10-27
