ServiceNow has acquired Moveworks—What does it mean for you?
ServiceNow’s acquisition of Moveworks brings uncertainty for enterprises. Customers may face pressure to standardize on ServiceNow, unclear product roadmaps for non-ServiceNow environments, limited flexibility for multi-platform organizations and potential price hikes as part of the consolidation strategy.
As the market shifts, forward-thinking enterprises are choosing Aisera as their strategic AI partner.
Now is the time to rethink your Agentic AI strategy.
Talk to an Agentic AI expert
Aisera Named a Leader in 2024 Gartner® Magic Quadrant™ for Artificial Intelligence Applications in IT Service Management
Comprehensive use-case support: Aisera addresses a wide set of AI applications in ITSM use cases within its offering. Customers can leverage Aisera’s proprietary LLM or bring their own models and use the LLM Studio to tune them with their own knowledge and ITSM data.
Trust-oriented messaging: To address customer security and privacy concerns, Aisera’s TRAPS (Trusted, Responsible, Auditable, Private, Secure) framework provides a balanced set of guiding principles to offer customers visibility into their approach to designing and deploying GenAI apps.
Why Fortune 500 companies chose Aisera
Aisera’s Agentic AI Platform serves as a unified, scalable foundation that streamlines employee productivity while seamlessly extending to industry-specific applications. From IT and HR to customer service, it drives automation, efficiency and intelligent interactions at scale.
Aisera’s multi-agent system orchestrates cross-functional AI agents, including third-party AI agents, to tackle complex enterprise use cases, delivering enterprise-wide benefits.
Aisera provides seamless deployment options across major cloud providers (AWS, Azure, GCP), VPCs, hybrid clouds, and on-premises environments, providing enterprises with agility and operational control.
Aisera Differentiators
Domain-Specific AI Agents
Delivers domain-specific AI agents trained on industry data for precise responses and actions, leveraging LLMs and SLMs to enhance accuracy and reduce errors.
Dynamic Action Agents
Creates enterprise-grade AI agents with guardrails using natural language, identifying and executing the right APIs in sequence to complete complex tasks on the fly. This eliminates the need for pre-defined workflows, enabling rapid request fulfillment and seamless task completion.
Voice Channels
Aisera’s AI Voice Agent resolves common customer questions on first contact, reducing wait times and delivering a natural, lifelike experience. Customizable and available 24/7, it offers instant help tailored to your needs.
Privacy and Data Protection
Employs the TRAPS framework that guarantees enterprise-grade privacy, data ownership, and security for customers.
LLMOps & LLM gateway
Optimize AI performance and cost with Aisera’s LLM Gateway—route queries intelligently and manage any LLM securely, including Aisera, third-party, or proprietary models.
Third-Party Agent Orchestration
Orchestrate multiple internal and external agents through a unified interface, eliminating the hassle of maintaining and managing multiple agents and enhancing the user experience.
One Platform for employees,
customers and agents
Boost productivity
Allow organizations to deliver self-service at scale, connecting systems across the enterprise into a unified interface that helps get work done
Offer 24/7 self-service support
Empower your customers with 24/7 self-service on any device of their choice
Maximize Agent Efficiency
Democratize agent knowledge and minimize repetitive tasks with case summaries, recommended actions, and AI-driven workflow automation—delegating live agent hand-offs to only the most complex issues
Battle of AI agents: introducing a new benchmarking framework for enterprise AI agents
The CLASSic framework provides a holistic benchmarking framework to evaluate enterprise AI agents and then performs a comparative evaluation of domain-specific AI Agents with AI Agents built directly on foundation LLMs.
The study found that domain-specific AI agents outperformed AI agents built directly using frontier LLMs, demonstrating the advantages of domain specialization in enterprise applications.
