Enhance content creation efficiency and consistency by allowing your team to access the AI tools they need directly
within your editor. No more jumping back and forth between external AI platforms and your app - CKEditor AI provides
all the AI writing tools needed to optimize the modern content creation workflow.
In this demo you can test CKEditor AI hands-on. Start a chat in the AI side panel and use the chat history feature to switch between different document conversations. Use the Review feature to run grammar and style reviews, or use Quick actions, like rewriting and summarizing, directly on the text inside the editor.
Operational Summary – Second Half of 2025
This report summarizes customer support performance during the second half of 2025. It focuses on ticket volumes, response efficiency and common issue categories, based on internal operational data across all support channels.
The information below should be treated as an overview of observed trends rather than a detailed performance evaluation.
The diagram outlines our internal customer support process, showing how incoming requests are handled across multiple support tiers based on complexity.
Customer inquiries are initially managed by Tier 1: Frontline Support, which is responsible for triage and resolution of common issues. More complex cases are escalated to Tier 2: Technical Support, where deeper technical investigation is performed.
High-impact or unresolved issues are handled by Tier 3: Escalation Team, which coordinates with internal experts as required. Specialist Teams support Tier 2 and Tier 3 by providing domain-specific expertise, while typically remaining non-customer-facing.
The process is designed to allow flexible movement between tiers, supporting efficient resolution and appropriate escalation when needed.
During the reporting period, the support team processed 184,600 tickets, representing an increase of 11% compared to the previous period. Ticket volume peaked in September and gradually stabilized towards the end of the year.
The increase was primarily driven by onboarding-related questions and product configuration requests.
| Channel | Share of Tickets | Change vs. Previous Period | Avg. First Response Time |
|---|---|---|---|
| 54% | -3% | 3.1 hours | |
| Live Chat | 31% | +5% | 1.2 hours |
| In-App Support | 15% | -2% | 2.4 hours |
Email remained the dominant support channel, although live chat usage continued to increase, particularly among larger accounts.
Average response and resolution times showed minor improvement compared to earlier in the year.
More complex cases, especially those related to integrations, required additional follow-up and were not consistently resolved within standard timeframes. While faster response times were generally appreciated, qualitative feedback indicates that communication consistency played an equally important role in overall customer perception.
"Faster responses were helpful, but consistency in follow-up communication had a bigger impact on our overall experience."
— Enterprise customer, post-resolution survey
The most frequently reported issues were:
Billing-related requests declined slightly, while integration-related inquiries increased towards the end of the period.
Customer satisfaction was measured through post-resolution surveys. The overall response rate remained stable throughout the reporting period.
Feedback most often referenced response time and clarity of follow-up communication as areas for improvement, particularly in cases involving multiple handovers or escalations.
Internal review identified several operational areas that may require further attention:
While these issues did not materially impact aggregate performance metrics, they were visible in individual case handling and customer feedback.
"The issue was eventually resolved, although it was not always clear who was responsible for the case during escalation."
— Key account feedback, quarterly review
Overall support performance remained within expected operational ranges. Most key indicators were stable, with moderate improvements observed in response efficiency. At the same time, the data suggests that further improvements in communication clarity and escalation handling could positively impact customer experience in future reporting periods.
Read more about the AI capabilities in the documentation.
Check the source code for this demo.
CKEditor AI supports several leading AI models:
New AI models are added regularly. Custom models are supported in the on-premise distribution - contact us to find out more.
Introduces an all-in-one AI-driven editing experience and review process inside your application without friction
Increases team productivity by reducing manual editing, review cycles, and context-switching delays
Enhances content quality, clarity, and brand alignment across large teams
Saves months of research and development by introducing drop-in AI writing features inside your app
Future-proofs the content pipeline with scalable AI features adaptable to evolving business goals
Offloads operational burden and reduces the workload of AIOps teams
Reduces costs associated with external copyediting, QA, or manual rewrites
Speeds up time to publish and supports real-time content personalization
Preserve organizational knowledge and reduce duplication with persistent AI chat history
CKEditor AI is a set of in-editor configurable AI features - AI Chat with chat history, AI Quick Actions, and AI Review - that enhance writing, formatting, and reviewing content.
Yes. All AI-generated changes are reviewable as suggestions before they’re applied.
CKEditor AI is designed as a drop-in, out-of-the-box component for applications using CKEditor 5. See the implementation guide for details.
CKEditor AI is offered as an add-on to existing editor plans, using a simple and scalable subscription-plus-usage pricing model. Customers choose from three service tiers, each with a fixed monthly or annual fee that includes a credit allowance for AI-powered actions. If customers exceed their monthly allowance, predetermined overage fees apply.
This comparison table will help you navigate the credit usage for different LLMs and specific operations.
The CKEditor AI on-premise solution is planned for Q1 2026. However, we're already testing it with selected customers and prospects. If you want to participate in the testing process of CKEditor AI on-premise, contact our sales team.
We start with models from three major providers: OpenAI, Anthropic, and Google Gemini. The LLM market evolves rapidly, so CKEditor AI has a built-in mechanism for the introduction of new models quickly, as long as they can support the features of the editor.
Not yet. However, we plan to have this available in Q1 2026 as a part of the on-premise solution.
CKEditor AI Assistant will still be available and maintained for our current customers. However, if you're looking to implement a more robust set of AI writing features inside your application, then CKEditor AI is the way to go.
The original AI Assistant is similar to Quick Actions in CKEditor AI. However, you can transfer AI Assistant actions to CKEditor AI.
No, it’s not. We take your data privacy seriously and never train our own models on your data. Your data remains yours.
Everything is stored in CKEditor Cloud Services and follows the same rules and patterns as other data we store for the editor features. For a full security breakdown, please visit the security section on our homepage. However, bear in mind that your queries to LLMs, together with all the data required to perform the operation, are processed by the selected LLM provider.
