How to Prioritize LLM Projects
Discover a practical framework to evaluate, rank, and scale impactful GenAI initiatives.
GenAI-Powered Email Categorization & Automation Engine
Transform customer engagement with real-time AI-powered email processing.
Reimagine customer email handling with GenAI. Xebia’s AI-powered engine categorizes, prioritizes, and drafts personalized responses in real time—boosting productivity and reducing triaging efforts by up to 95%. Integrated with your CRM, it unlocks faster resolutions, smarter engagement, and new revenue opportunities—turning every email into a moment of business impact.
Xebia’s GenAI Email Categorization and Automation solution transforms inbound customer email management with powerful Large Language Models (LLMs) and seamless CRM integration. The platform rephrases queries for clarity, categorizes them by intent and urgency, maps them to the right business unit—sales or service—and recommends the next-best actions. It fetches real-time customer insights from CRM systems to personalize and accelerate responses. With contextual summarization, automated drafting, and human-in-the-loop review, enterprises can reduce triaging effort by up to 95%.
Unlock faster resolutions, increase upsell opportunities and ensure smarter service delivery at scale with Xebia's end-to-end expertise that transforms how enterprises handle customer engagement.
Our Approach
Email Interception and Preprocessing
Intercepts inbound emails from various customer channels and initiates the processing pipeline.
1
Intent Rephrasing and Context Enrichment
LLMs refine and standardize customer queries by rephrasing them for clarity and better understanding, analyzing and rewriting raw emails into structured representations to improve downstream categorization accuracy.
2
Email Categorization into Business Units
LLMs use prompt engineering and classification capabilities to determine if the query relates to Sales, Service, Support, Billing, etc.—tagging each email with department-level categories using semantic understanding and domain-specific fine-tuning.
3
Action Determination and Prioritization
LLMs infer the next-best action based on email content and context—escalating, replying, assigning, or requesting additional information—by identifying necessary tasks for support staff or systems based on urgency, intent, and customer sentiment.
4
CRM Validation and Data Augmentation
LLMs are not directly involved; CRM integration enables context injection into the LLM. This step retrieves customer details, history, and service level to enrich the context for drafting responses.
5
Response Drafting
LLMs craft personalized, accurate, and on-brand email responses using prior context and customer history—generating replies tailored to the customer’s intent, tone, and account information, optionally including summaries of previous threads.
6
Human-in-the-Loop Review (Optional)
LLMs provide confidence scoring or suggestive edits to aid human agents in approving or modifying AI-generated drafts, adding explainability, transparency, and editable options for sensitive or high-impact communications.
7
Email Dispatch and CRM Logging
LLMs are not directly involved; the output of the LLM is handed off to automation systems. The final response is sent to the customer and logged in the CRM or ticketing system.
8
Continuous Learning and Feedback Loop
LLMs train on accepted responses and rejected suggestions to improve future output quality and reduce human intervention—learning from interactions, feedback, and effectiveness to enhance accuracy and personalization.
9
Key Benefits
Reduce Manual Email Processing
Automate repetitive triaging and free teams to focus on complex interactions.
Real-Time Routing and Prioritization
Ensure high-priority customer needs are resolved without delay.
Minimize Missed Opportunities
Surface revenue-driving interactions instantly with AI-based urgency detection.
Better Resource Utilization
Reduces dependency on large support teams by offloading repetitive, low-complexity queries to AI, allowing staff to focus on high-value tasks.
Increase Conversion and Upsell Opportunities
Identifies sales intent in service-related emails and surfaces opportunities for cross-selling and upselling.
Enhance Business Insights
Provides structured metadata from unstructured emails (e.g., query type, sentiment, urgency) for better decision-making and analytics.
Consistency and Compliance
Ensures brand-compliant and policy-aligned communication across every response, reducing reputational and legal risks.
Our Ecosystem
Partners
Our Ideas
Insights & Perspectives
Dataset Enrichment using LLM’s
LLMs can help extract valuable information from unstructured data like text.
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Advanced LLM Applications
Learn how to master the latest LLM tools and techniques, optimize performance, and build sophisticated AI applications.
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