Gen AI augmented customer care agent 

Your existing chatbot handles self-service - it works without a human in the loop. The Gen AI Augmented Customer Care Agent is designed for the moment a customer reaches a live agent: it listens to the conversation in real time, retrieves the right knowledge, and surfaces suggested responses and next-best actions directly to the agent's screen. The two are complementary. In fact, THIS has designed this solution to be integration-friendly and API-first, so it can sit alongside your existing chatbot layer and take over seamlessly when calls are escalated or routed to a human agent - a common scenario in complex Telco billing disputes, bank onboarding queries, or energy contract renegotiations.

The solution includes a built-in admin console and governance dashboards that give your compliance and operations teams full visibility into how the AI is performing, what content it is retrieving, and what recommendations it is making. The LLM responses are grounded in your own enterprise knowledge base and policy repositories - not open-ended generation - which significantly reduces hallucination risk. For regulated sectors like Middle Eastern banking or European energy, this grounding approach means the AI only surfaces information you have explicitly approved, making it far easier to demonstrate compliance to regulators such as the FCA, SAMA, or ACER.

Microsoft Azure Speech to Text, which powers the real-time transcription layer of this solution, supports a broad range of languages and regional accents, including Arabic, French, German, and English variants. The LLM layer via Microsoft Azure OpenAI also handles multilingual prompting and response generation. THIS can work with your team during implementation to configure language models and knowledge bases per market, so an agent handling a call in Riyadh gets Arabic-grounded guidance, while one in Paris receives French-language recommendations - from the same underlying platform.

Based on results delivered for a leading business process services provider, THIS documented a 40% increase in agent efficiency, a 50% reduction in Average Handle Time (AHT), a 45% improvement in resolution rates, and a 70% reduction in call transfers — all within the live production environment. For Telcos with high call volumes, the AHT reduction alone translates directly into significant cost savings and capacity release. For banks and FinTechs where first-call resolution directly impacts customer retention, the resolution rate uplift is particularly material. THIS will work with you to baseline your current metrics and project client-specific ROI ahead of deployment.

The solution is built API-first. The AI orchestration layer retrieves customer context, order data, account history, and product information directly from your backend systems via API calls during the live call — so the agent sees a unified, contextualized view without toggling between screens. For Telcos, this means the agent can see a customer's current plan, usage, and open tickets in real time. For energy companies, it means tariff details and meter data are surfaced instantly. THIS has extensive integration experience across enterprise platforms and can connect to your existing CRM, BSS/OSS, or core banking systems as part of the implementation.

A traditional knowledge base requires the agent to formulate a query, search, read through results, and then craft a response — all while the customer is waiting. The Gen AI Augmented Agent eliminates that cognitive burden entirely. It continuously monitors the conversation, automatically identifies what information is needed, retrieves the right content, and generates a ready-to-use suggested response or action. The agent validates and delivers it. This is the difference between an agent spending 3–4 minutes searching during a call versus receiving a grounded answer in seconds - which is precisely how AHT was cut by 50% in the documented case study.

The Gen AI Augmented Customer Care Agent represents a deliberate and proven first step on the agentic journey - human-in-the-loop augmentation, where AI handles retrieval, reasoning, and recommendation while the human agent retains control and accountability. This is the right starting point for regulated industries. Once your organization has validated AI performance, built trust in the recommendations, and established governance frameworks, THIS can help you progressively shift tasks toward greater autonomy — for example, enabling the agent to trigger backend actions (case creation, refund initiation, plan changes) directly from the AI-recommended workflow. The modular, extensible architecture is designed specifically to support this evolution.

No. The solution is built natively on Microsoft Azure - Azure Speech to Text for real-time transcription and Azure OpenAI for LLM-driven response generation and recommendations. If you are already an Azure customer, which is common across European Telcos, Gulf banks, and global FinTechs, this solution fits directly into your existing cloud governance, data residency, and security frameworks. There is no requirement to onboard a separate AI vendor, and your existing Azure agreements and enterprise licensing may apply.

The solution is explicitly designed as an augmentation tool, not an automation replacement. The agent remains the primary interface with the customer at all times — the AI assistant operates in the background, surfacing suggestions that the agent chooses to act on. In practice, agents quickly recognize that the tool reduces their cognitive load and makes them look more competent and responsive, which drives organic adoption. The measurable 25% increase in agent utilization seen in the case study reflects agents handling more interactions more confidently - not being replaced. THIS includes change management and training support as part of its implementation approach.

The solution is productized and modular - core components including the transcription engine, AI orchestration layer, LLM response engine, web UI, and admin console are pre-built and configurable rather than built from scratch. For an existing THIS client, the implementation timeline is typically accelerated because integration patterns, security protocols, and enterprise context are already established. A phased rollout is standard: initial deployment in a controlled agent group to validate performance against your specific use cases, followed by broader rollout with continuous improvement driven by dashboard insights. THIS will scope a delivery plan tailored to your contact center scale, language requirements, and backend integration complexity.