Real time AI assist for contact centre agents

In Bradesco's collections operation, a generative AI system analyzes 18,000 calls a day and guides the human operator on what is likely to work, such as what to say, when to offer a product, which product and on what terms, so the operator negotiates better with a customer who has a debt. Bradesco's director of Bradesco Experience described the initiative at the Bloomberg Línea Summit 2025 in São Paulo, as part of a wider generative AI program that also runs the bank's BIA customer chat and an internal coding assistant.

CaixaBank's GenIAl project put five generative AI use cases into production and, in August 2024, the bank launched a second phase, GalaxIA, to scale them across the group, including the Portuguese subsidiary BPI, VidaCaixa and CaixaBank Payments and Consumer. Two of the five are a Contact Centre assistant that gives the human agent more and better context aware information about the customer and helps with specific tasks such as blocking a card, and a Customer Service Management (CSM) tool that identifies and classifies complaint cases and assists the specialised teams that handle them. CaixaBank describes GenIAl as having exceeded expectations and reached production, but the release gives no quantified figure for either use case.

DBS built CSO Assistant in house for its 500 customer service officers in Singapore, who handle queries from more than 250,000 customers a month. It combines a language model tuned to local languages and parlance with telephony and speech recognition: it transcribes the call in real time, searches the knowledge base live, then writes the call summary and prefills service request fields. Pilots began in October 2023; full rollout in Singapore was planned before the end of 2024, followed by Taiwan and Hong Kong. The 20% cut in call handling time in the release is an expectation, not a result.

SK Telecom built an AI Customer Service Support System on its own telecommunications specialized large language model (Telco LLM) and large multimodal model (LMM), trained with input from dozens of customer service experts over about a year. The system gives agents an AI Knowledge Search Assistant that answers natural language questions instead of manual lookup, an LMM powered Intelligent Document Processing feature that classifies customer submitted documents, and an Automated Post-Processing feature (planned at the time of the announcement) to summarize consultation outcomes. It completed a month long beta test starting in mid October before this announcement.

Achieve, a digital personal finance company that runs long term debt resolution programs, deployed Cresta to give agents real time guidance through difficult client conversations and to auto generate call summaries, alongside a behavior based coaching hub for its leadership team. Brandon Peterson, SVP of Client Experience and Operations, says consistency across every call is central to keeping clients in a program that only pays off if they stay enrolled. He says after call work fell by 75 percent, almost immediately.

Aqua Finance, a US consumer lender for home improvement, water treatment and recreational vehicle purchases, rolled out Cresta across its servicing operation, with a focus on collections. The platform surfaces real time hints during calls, auto generates call summaries, live transcribes and translates for bilingual and offshore agents, and scores 100 percent of calls for coaching instead of a small sample. Cresta also reports a 50 percent cut in after call work in collections. Dan Greer, SVP of Servicing Operations, says the goal was to lift every agent's performance without adding headcount as loan volume grew.

CIMB Niaga, one of Indonesia's largest banks, built purpose built AI agents with its AI Center of Excellence and Artefact on Google Cloud. A Relationship Manager AI Agent helps advisory staff offer tailored advice and proactive guidance matched to a customer's financial goals and life stage, and a Contact Center AI Agent works alongside service staff during live customer interactions, surfacing the procedural and product information they need from the bank's knowledge management system instead of making them search for it. No outcome figures were published.

Definity, the parent of several Canadian property and casualty insurers, worked with Deloitte to use Google's AI in its contact centre: summarizing calls, automating caller authentication, analyzing customer sentiment and giving team members real time recommendations. Calls are transcribed, passed through data loss prevention and summarized by language models, with the summaries stored in Salesforce. Definity says automated summaries cut three and a half minutes from each call within about a month; Google Cloud reports shorter call handling times and higher productivity overall.

Discovery Bank, the digital bank inside South Africa's Discovery Group, built an AI assistant on Azure OpenAI Service that gives its contact centre agents personalized client insights and product and process information through a chat interface during live client interactions, replacing manual lookups. The bank says the assistant has shortened new agents' training time and that agent feedback on the tool has stayed positive and improved over time. Discovery Bank reports that this assistant, together with its wider Databricks based data platform, delivered a 500% return on investment, though that combined figure is not isolated to the agent assistant alone.

SEB, a Nordic corporate bank, worked with Bain & Company to build an AI agent on Google Cloud for its wealth management division. The agent suggests responses during conversations with customers and generates call summaries afterwards. Google Cloud reports a 15% efficiency gain.

SIGNAL IDUNA, a German insurer, built Co SI with Google Cloud, BCG and Deloitte: a knowledge assistant that helps customer service agents answer complex health insurance questions. Google Cloud reports that for less experienced agents, information searches are 30% faster and inquiries that previously needed further escalation dropped from 27% to 3%.

Singapore Airlines is incorporating Salesforce Agentforce, Einstein in Service Cloud and Data Cloud into its customer case management system so that customer service representatives get a summary of a customer's previous interactions with the airline together with guidance on how to help, instead of having to piece the history together themselves. The two companies also plan to co develop further AI solutions for the airline industry at a Salesforce AI research hub in Singapore.

Singapore Airlines' chief executive said the airline had developed more than 250 generative AI use cases and implemented around 50 initiatives across its end to end operations in the 18 months before this announcement, but that programme wide figure is not a measured result of this specific Agentforce deployment.

AIA, the pan Asian life insurer, rolled out Copilot in Microsoft Dynamics 365 Customer Service to its contact centres in Singapore and Thailand in 2024, after an assessment that covered fairness and bias, user friendliness, time savings and security. Copilot summarises a customer's case history and live chat conversations for the agent automatically, so the agent no longer has to search scattered emails and notes to piece together the account history, and it drafts suggested replies to customer emails for the agent to review. AIA is expanding Copilot to more markets across Asia and is also rolling out Copilot Studio for self service.

Aptive Environmental, a pest control company, used Cresta's real time agent assist across its contact centre to standardize how agents handle cancellation and renewal calls. Cresta surfaces hints during the call that guide agents through discovery of why a customer wants to cancel, then suggests tailored offers in the sequence most likely to retain the customer, alongside consolidated call review and transcription for supervisors. Two years after deploying Cresta, Aptive reports a higher save rate on cancellation calls and higher adherence to its empathy and discovery playbook.

Oportun, a US consumer lender, replaced manual, sample based QA with Cresta's AI quality management across all calls, combined with real time guidance for agents. Coaching now focuses on the behaviours that drive performance, visible across every call, instead of a small sample reviewed weeks later. No quantified outcome is published.

When a customer calls Porto Seguro, the service agent uses generative AI to pull up the customer's policy and contract information during the call instead of searching for it manually. Agents were trained to ask the right questions, and the AI's lookup of contract data reached 80% accuracy in May 2024. Porto's goal is a fully self service digital version of the same lookup for customers who do not want to speak to a human.