Shriram Sankaran![Accelerate Document Writing, Editing, and Review with AI-Powered Workflows [Webinar Show Notes]](https://www.syncfusion.com/blogs/wp-content/uploads/2026/05/Accelerate-Document-Writing-Editing-and-Review-with-AI-Powered-Workflows-Webinar-Show-Notes-scaled.png)
Modern applications need document experiences that don’t force users to jump between tools. In this webinar, we explored a React document workspace where AI is embedded directly into the editor to help users:
- Draft content faster with prompt-based generation.
- Improve selected text with rephrasing, translation, and grammar correction.
- Review long documents by using generated summaries.
- Ask document-specific questions with contextual Q&A.
- Stay in control with a review-first user experience that provides compare, keep, regenerate, and discard actions.
If you missed the webinar or would like to review it, the recording has been uploaded to our YouTube channel and is embedded below.
Why AI-powered document workflows are important
In many apps, document tasks are still fragmented: users leave the editor to use separate AI tools to draft, rewrite, fix grammar, translate, summarize, or ask questions. That context switching slows productivity and breaks focus.
When you embed AI inside the document workflow, help appears exactly where users need it without interrupting the writing experience.
Demo
The demo React app used the Syncfusion React DOCX Editor as the primary workspace. In it, users could:
- Upload an existing Word document or create a new document.
- Enable AI by using a simple AI toggle.
- Use two AI entry points, depending on their need:
- Inline assistant (in-document) for drafting and editing actions.
- Chat assistant (side panel) for summarization and document Q&A.
In the demo, the side panel was built using the Syncfusion React AI AssistView component.
This design followed a simple workflow used throughout the session: Generate → Refine → Summarize → Ask.
Prerequisites
- A React project.
- A Syncfusion license key.
- Access to an AI service, such as Azure OpenAI.
What the demo covered
Setting up the Syncfusion React DOCX Editor
The editor was configured using DocumentEditorContainerComponent with the ribbon toolbar enabled. This provides a browser-based, Word-like workspace for creating, editing, formatting, and reviewing documents within a React application.
Configuring the AI gateway
The demo routes all AI features through a single helper function that sends chat messages to Azure OpenAI and returns the model’s response. Reusing the same helper across generation, refinement, summarization, and Q&A keeps the implementation consistent and easy to extend.
The session also highlighted a bring-your-own-key approach for AI integration. While the demo used Azure OpenAI, the same pattern can be adapted to other AI services without changing the editor workflow by updating the AI configuration.
Inline AI (generate and refine)
- Content generation: With no text selected, users can enter a prompt and shape the output by using tone, format, and length controls. The generated draft is reviewable, users can keep, regenerate, or discard the draft before anything is written to the document.
- Rephrasing: Selecting text and choosing this option opens a side-by-side comparison dialog. Users can cycle through multiple suggestions and choose the one they’re satisfied with.
- Translation: A target-language picker lets users preview the translated output before applying it. Changing the language refreshes the preview automatically.
- Grammar correction: Users can run either a general cleanup or select specific grammar checks. The corrected output appears in a review dialog before replacement.
Document-level AI (summarize and ask)
- Summarization: Users can open the chat assistant and select Summarize this document. The app extracts the full document text, sends it to Azure OpenAI, and returns a concise summary in the chat panel.
- Follow-up suggestions: After summarizing, the assistant suggests follow-up questions to help users explore the document further.
- Context-aware Q&A: Users can ask a direct question and receive an answer grounded in the document’s content, rather than a generic response. Answers can be copied or inserted directly into the document.
Data privacy and security
In this embedded approach, AI requests are routed through your application, so you control what is sent, where it is processed, and how it is governed. This makes the pattern well-suited for enterprise workflows where privacy, compliance, and policy controls matter.
Timestamps
- [00:00] Welcome and webinar introduction
- [00:21] The problem with fragmented document workflows
- [01:45] The AI workflow model: Generate, refine, summarize, ask
- [02:43] Poll: Biggest document workflow challenge
- [03:20] Overview of the AI-powered editor experience
- [04:07] Demo prerequisites and setup
- [04:22] Generate and refine workflow introduction
- [05:17] Creating a new document in the React DOCX Editor
- [05:42] AI content generation demo
- [06:41] Reviewing and regenerating AI-generated content
- [07:02] Rephrasing selected content
- [07:46] Translation workflow demo
- [08:07] Previewing multilingual content before accepting it
- [08:10] Grammar correction workflow
- [09:10] Why embedded AI feels more natural in editing workflows
- [09:27] Connecting the workflow to the React implementation
- [10:05] Setting up the Syncfusion React DOCX Editor
- [10:38] Configuring the Azure OpenAI integration
- [11:34] Bring your own AI provider model
- [11:55] Building inline AI entry points
- [12:44] Context-aware AI behavior based on selection
- [13:26] Prompt-driven content generation flow
- [14:09] Reviewing generated drafts before insertion
- [14:31] Tone, format, and length customization
- [15:10] Sending prompts to Azure OpenAI
- [15:44] Refinement workflows and contextual menus
- [16:22] Side-by-side comparison dialog for review
- [17:12] Stopping AI generation when needed
- [17:44] Replacing selected text programmatically
- [18:27] Grammar correction implementation
- [19:45] Translation workflow implementation
- [20:42] Document-level AI assistance introduction
- [21:21] Uploading a document for summarization and Q&A
- [21:35] AI-powered document summarization demo
- [22:17] Contextual Q&A demo inside the document
- [23:05] Connecting document workflows to implementation
- [23:49] Building the AI chat assistant panel
- [24:09] Extracting full document text for summarization
- [25:07] Generating follow-up questions automatically
- [25:37] Building contextual Q&A with document-aware prompts
- [26:42] Copying and inserting AI responses into documents
- [27:08] Poll: Biggest benefit of embedded AI workflows
- [27:36] Privacy, security, and enterprise considerations
- [28:17] Key takeaways from the session
- [29:06] Closing remarks and next steps
Q&A
Q: In this solution, will the LLM key be exposed to the user when browsing the React app’s source?
A: Yes. Because the React app runs in the browser, the LLM key included on the client side becomes visible in the source code. This makes it accessible to anyone using the application, which is a security risk. A safer approach is to store the key on the server and let the React app communicate with your back end, which then securely calls the LLM API.
Q: If the LLM key is bundled with the client, is the only secure option to handle calls through a server?
A: Yes. The secure solution is to keep the key on the server and let the back end make the LLM API call. The client should only send requests to your back end, while the back end, holding the key in environment variables, calls the LLM and returns the response. This way, both the key and the LLM invocation remain hidden on the server side.
Q: Can you control the grade level of the language generated in the document?
A: Yes. You can adjust the language level by controlling tone, vocabulary, and sentence complexity. The application already provides tone options, and if more precise grade-level control is needed, you can extend the application to include settings that define grade-specific language rules.
Key takeaways
- AI is most effective when embedded into workflows, not separated into another tool.
- Different document tasks need different interaction patterns:
- Prompt-based generation.
- Selection-aware refinement.
- Chat-based summarization and Q&A.
- Trust matters: A review-first UX (compare, regenerate, discard, replace) keeps users in control.
- A single AI gateway keeps the solution consistent and extensible.
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