Aisera
Level 11: IT Operations, Networking & IT Service Management
Engineering & Operations · Level 11
In short
Aisera is an AI tool in the IT Operations & ITSM category from Aisera, Inc. in Palo Alto, United States. The pricing model is paid. It is with an English interface that handles German content.
What is Aisera?
Aisera is an enterprise AI platform specializing in generative AI service management and automated workflow execution across IT, customer service, and HR. The platform leverages autonomous AI agents, domain-specific large language models (LLMs), and deep integrations with enterprise systems such as ServiceNow, Salesforce, Jira, and Workday. By automating multi-step resolution processes, Aisera enables organizations to resolve routine support requests instantly without human intervention.
The architecture combines self-service AI agents for end-users with AI copilots designed to assist human support representatives in real time. Aisera analyzes incoming tickets, executes context-aware workflows—such as resetting passwords or managing access requests—and routes complex issues to the appropriate teams. Embedded Trust, Risk, and Security Management (TRiSM) guardrails ensure data privacy, compliance, and hallucination control across all interactions.
Enterprises deploy Aisera to drastically reduce mean time to resolution (MTTR), lower operational service desk costs, and improve overall user satisfaction metrics. The system offers pre-built industry domain models along with no-code workflow orchestration tools and robust API connectivity. As a result, it seamlessly scales within complex IT ecosystems while continuously learning from interaction history.
Core features & strengths
- Autonomous AI Agents — Generative AI agents handle end-to-end resolution for IT, HR, and customer service inquiries by executing actions in connected systems. They resolve routine user requests autonomously without requiring human agent involvement.
- Agent Assist Copilot — Support representatives receive real-time answer suggestions, automated conversation summaries, and next-best-action guidance during live support cases. This speeds up overall ticket handling and increases first-contact resolution rates.
- Domain-Specific LLMs & TRiSM — The platform utilizes specialized domain LLMs coupled with enterprise-grade guardrails for security, trust, and hallucination reduction. This ensures precise responses while maintaining strict data governance across enterprise workflows.
Who is this tool for?
Aisera is designed for medium to large enterprises and global organizations managing high volumes of IT, HR, and customer support tickets. It is ideal for operational teams looking to modernize their service management through agentic AI and workflow automation.
Typical use case
An enterprise deploys Aisera as a unified IT and HR service desk integrated within Microsoft Teams. When an employee requests access to a restricted software tool via chat, Aisera validates their role against HR policies in Workday and triggers an automated provisioning workflow in Jira. The entire request is resolved in seconds without manual intervention from IT administrators. This eliminates ticket backlogs and significantly boosts productivity.
What is Aisera good for?
- Aisera is designed for medium to large enterprises and global organizations managing high volumes of IT, HR, and customer support tickets. It is ideal for operational teams looking to modernize their service management through agentic AI and workflow automation.
- An enterprise deploys Aisera as a unified IT and HR service desk integrated within Microsoft Teams.
- Autonomous AI Agents: Generative AI agents handle end-to-end resolution for IT, HR, and customer service inquiries by executing actions in connected systems. They resolve routine user requests autonomously without requiring human agent involvement.
- Agent Assist Copilot: Support representatives receive real-time answer suggestions, automated conversation summaries, and next-best-action guidance during live support cases. This speeds up overall ticket handling and increases first-contact resolution rates.
- Domain-Specific LLMs & TRiSM: The platform utilizes specialized domain LLMs coupled with enterprise-grade guardrails for security, trust, and hallucination reduction. This ensures precise responses while maintaining strict data governance across enterprise workflows.
When a different tool fits better
Small businesses or startups with low ticket volumes will likely find Aisera's enterprise platform over-engineered and cost-prohibitive. Organizations seeking a basic website FAQ chatbot without the need for enterprise system integrations should consider simpler alternatives.
Pricing & plans
Plans in detail
- EnterpriseContact salesContact salescustom
- AI-powered service automation
- Seamless integration with enterprise systems
Good to know
- No public pricing plan available.
- Free trials or demos are provided upon request via the sales team.
- Pricing depends on license count and feature scope.
Prices checked on 15/08/2026. Prices based on public provider information, without warranty. Euro amounts are approximations; the provider's pricing page prevails.
Supported languages
Interface = the tool's menu language, content = the language you can work in. Without guarantee — vendors keep expanding their language coverage.
Privacy & GDPR
Data flow: Data is sent to Aisera and, depending on configuration, to connected enterprise systems, cloud services, or selected LLM providers; hosting location and governing jurisdiction should be confirmed in the quote and DPA.
Training on your inputs: The supplied vendor excerpts do not clearly establish whether customer content is used for model training by default or what opt-out rules apply, so this should be confirmed in writing before contracting.
For companies: Organizations should execute an enterprise agreement and DPA covering subprocessors, data location, retention, deletion, security, and any connected model providers.
Practical advice: Enter only data approved for the agreed purpose, and avoid highly sensitive, confidential, or personal information until permissions, retention, data flows, and contractual safeguards have been verified.
- GDPR:
- EU data protection regulation: defines how personal data may be processed and what rights you have (access, deletion, objection).
- DPA:
- Data Processing Agreement: contractually binds the provider to process your data only on your instructions. Usually mandatory for companies.
- SOC 2:
- Independently audited security report (access control, availability, confidentiality) — not a privacy seal, but a sign of professional IT security.
- Opt-out:
- Training on your data is on by default; you have to switch it off yourself in the settings.
- Training on user data:
- Your inputs may feed into future model versions. Confidential content could in theory resurface in other users' answers.
Privacy data checked on 31/07/2026. Editorial summary based on public provider information — not legal advice. When in doubt, check the provider's current privacy terms.
Fact sheet
| Vendor | Aisera, Inc. |
|---|---|
| Headquarters | Palo Alto, United States |
| Category | IT Operations & ITSM |
| Pyramid level | Level 11 – IT Operations, Networking & IT Service Management |
| Pricing model | Paid |
| Free forever option | No |
| Open Source | No |
| Entry plan | Enterprise: Contact sales (Contact sales) |
| German | content only, English interface |
| English | interface and content |
| Privacy classification | Unclear |
| Data processing agreement | Organizations should execute an enterprise agreement and DPA covering subprocessors, data location, retention, deletion, security, and any connected model providers. |
Alternatives to Aisera
- Ansible Lightspeed (Red Hat) — Paid · HQ: Raleigh, United States · GDPR / EU
- Atlassian Intelligence (Jira Service Management) — Paid · HQ: Sydney, Australia · Unclear
- Cisco AI Assistant — Paid · HQ: San Jose, United States · Unclear
- Datadog Bits AI — Paid · HQ: New York, United States · Unclear
- Dynatrace Davis AI — Paid · HQ: Waltham, United States · Unclear
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