Automate Customer and
Client Correspondence l
Customers expect to be able to contact you on multiple channels. Phone, mail, email and social media messaging can create high volumes of customer service requests that need to be triaged and responded to or referred on to specialist teams for assistance. These high volumes of unstructured customer correspondence can demand large contact centre teams and risk complaints if not responded to quickly. X-Comms delivers Ai-enabled analysis of customer service requests across any channel; voice, scanned mail, email, web chat, even video. Automated responses or onwards referral for complex service requests can then be issued, much more quickly and exceeding people-based quality levels.
Processing unstructured requests requires substantial human resources, leading to high operational costs and high employee churn
Managing customer requests across various channels like voice, email, and social media often leads to inconsistent response quality.
Customers can experience significant delays creating failure demand with repeat enquiries
Unstructured data from multiple channels is hard to track, analyse, and derive actionable insights from, making it challenging to improve customer service processes and outcomes.
AI-driven automation for analysing, classifying, and responding to communications without human intervention at virtually limitless scale.
Seamless integration with email, social media, and voice channels.
Real-time content detection and sentiment analysis for accurate, empathetic responses.
Scalable to handle growing volumes of communications efficiently.
Ensures data security and compliance with industry standards.
Customisable workflows and detailed analytics for continuous improvement.
Ai-driven analyses of client or customer correspondence, using either common Large Language Models (LLM), such as Chat-GPT, or the Aivantor private LLM service, to extract customer metadata, provide a summary, sentiment, and categorise the fulfillment required.
Automatically categorise the type of correspondence, 'Enquiries', 'Feedback', 'Complaints' etc using a private trained Natural Language Processing (NLP) model, which can be tailored to your organisation.
Make the extracted data available to other systems and services through our Application Program Interfaces (APIs).
Automatically respond to the customer, or forward the correspondence to the appropriate team for action.
Continuous self-learning from new data and feedback to enhance performance.
Integrates with existing systems to streamline communication management.
Up to 95% accurate extraction of customer data.
Up to 45% of incoming unstructured customer correspondence responded to automatically.
Target customer satisfaction scores of circa 80%