Meet Deepdesk, a company providing agent-assist solutions for large contact center operations.<\/p>\n
Specifically, its platform analyzes past customer conversations to generate knowledge and real-time recommendations for agents, helping them respond more effectively to customers across various channels, such as chat and email.<\/p>\n
To do this, Deepdesk calls upon large language models (LLMs), providing a copilot-like experience that improves the efficiency and quality of customer service interactions.<\/p>\n
Additionally, the voice feature exclusively uses a Gen AI model to offer suggestions.<\/p>\n
This makes the more accessible\u202fas there is no requirement for a large amount of historical call records to get started.<\/p>\n
Yet, Deepdesk doesn\u2019t attach contact centers to a specific LLM. Instead, its clients can bring or select their own models to drive up accuracy and drive down costs.<\/p>\n
That\u2019s one differentiation from the many similar AI solutions flooding the market.<\/p>\n
However, Deepdesk offers others, which have helped the provider reel in many big-name brands, like DHL, Vodafone, and Swisscom.<\/p>\n
Many agent-assist solution providers promise to do the same things. That\u2019s why many service desks deploy whatever their primary contact center or CRM provider offers.<\/p>\n
Yet, according to Robbert Dijkstra, Founder and CEO of Deepdesk<\/strong>, his company stands apart for three core reasons: advanced functionality, tech unification, and composability.<\/p>\n Consider that advanced functionality first. Alongside next best actions, proactive knowledge suggestions, and auto-summarizations, Deepdesk can offer some unique features.<\/p>\n For instance, it can recognize and autocomplete repetitive procedures and conversations on an agent\u2019s behalf, saving them considerable time.<\/p>\n Moreover, Deepdesk can automatically capture important details from the call, which the live agent can refer back to at any given time.<\/p>\n \u201cWe\u2019ve been working with larger organizations to create a product that works for all contact centers,\u201d explained Dijkstra. \u201cWhere others offer a few capabilities, we can offer more functionality.\u201d<\/p>\n Additionally, the CEO noted:<\/p>\n \u201cWe have a platform where you can unify CRM and contact center solutions.\u201d<\/p><\/blockquote>\n Take DHL, for instance. Deepdesk pulls relevant contact center data for each query into the CRM interface, minimizing toggling, lowering handling times, and enhancing the agent\u2019s experience.<\/p>\n In this example, the provider\u2019s composability also comes to the fore.<\/p>\n Dijkstra underscored this composability as one of Deepdesk\u2019s key strengths. \u201cYou can bring the whole contact center towards the CRM system people use,\u201d he said.<\/p>\n While Dijkstra also positioned the solution as scalable and future-proof, it\u2019s this composability that\u2019s particularly noteworthy.<\/p>\n \u200b\u200b\u200bComposability enables businesses to leverage elements of their existing setups, easing common constraints around integrations.<\/p>\n A key component is that Deepdesk are able\u202fto sit on top of the full CX tech stack and push information from any of them to the agent view.<\/p>\n It can also pull information from the conversation\u202finto other systems without\u202fthe agent needing to take any actions.<\/p>\n \u201cWe find that many of our enterprise\u202fcustomers have a combination of new tech and legacy\u202ftech, and performing actions like this are cumbersome or require complex interactions.\u201d<\/p><\/blockquote>\n Deepdesk\u2019s virtual assistant is composable, and \u2013 unlike its competitors \u2013 isn\u2019t constrained to a specific application or ecosystem.<\/p>\n As such, customers can have a copilot-esque interface where employees ask questions and receive pertinent insights\u202ffrom any connected system in the flow of their work.<\/p>\n But, Deepdesk doesn\u2019t only rely on LLMs. It also harnesses machine learning algorithms to continually enhance the performance of its agent-assist applications.<\/p>\n Although\u200b,\u200b LLMs are a \u200blong standing\u200b\u200b \u200barea of expertise for Deepdesk. \u201cUtilizing ChatGPT-2 in 2021, we were \u2013 and still are – ahead of the market in terms of features and capabilities,\u201d confirmed Dijkstra.<\/p>\n As noted, Deepdesk serves large enterprises, helping them optimize customer support.<\/p>\n Now, it\u2019s continuing its work integrating agent-assist apps to \u200bsupport voice-based interactions.<\/p>\n Deepdesk started with the digital channels in 2020 but have built out a robust feature set for the voice channel which\u202fis being used by many customers.<\/p>\n The ultimate goal is to \u201ctake out a lot of the repetition of typical questions people have.\u201d<\/p>\n Meanwhile, Deepdesk increases agent confidence by providing a mission-critical support mechanism during customer interactions, enabling them to steer conversations in a \u201cfulfilling direction.\u201d<\/p>\n Overall, Deepdesk strives to \u201cincrease the quality of the conversations\u201d contact center agents have with their customers and \u201creinforce\u201d its core philosophy: think human.<\/p>\nComposability and AI Agent Assist Go Hand in Hand<\/h2>\n
Deepdesk Takes on the Enterprise<\/h2>\n