Proven Results with SupportLogic
35%
REDUCTION IN ESCALATION RATES
98%
SEARCH ACCURACY (UP FROM (80%)
4%
REDUCTION IN MONTHLY CASE VOLUME
A long-time SupportLogic customer, NICE had already achieved measurable success using Core SX for sentiment detection, escalation prevention, and proactive support operations. The partnership helped NICE strengthen visibility across its support environment and reduce firefighting.
Building on that foundation, NICE saw an opportunity to go further, applying SupportLogic’s Resolve SX, Precision RAG, and Assist modules to unify fragmented knowledge sources, automate insight generation, and elevate the customer experience through AI-driven knowledge management and higher case deflection.
After deploying Resolve SX in the customer portal, NICE expanded to include internal knowledge sources and integrated SupportLogic into its internal workflows:
- Salesforce internal portal: Provides agents with the same generative search experience within Classic, returning summarized, referenced results across all sources.
- Microsoft Teams integration: Allows engineers to mention SupportLogic AI directly in chat and receive a generative, reference-linked answer – reducing the need to switch systems and accelerating resolution time.
This innovation is now extending benefits to NICE’s internal users, who generate 20–30% of total cases, and driving stronger collaboration with R&D.
“Resolve SX does the magic of deciding which source is best correlated and when to show results. It’s automation we simply couldn’t have built ourselves.”
Chris Romrell, Global Head of Technical Support, NICE CXone
How NICE Transformed their Knowledge Experience
NICE’s support organization relied on 12 to 13 different knowledge sources spread across multiple product documentation sources, Knowledgebase articles, and legacy systems. Finding the right information required constant searching, switching tools, and validating sources.
- Customers struggled to self-serve and often opened cases without finding answers.
- Legacy Search Experience provided a list of links, with less than a 50% click-through rate.
- Only 15% of customers used search before creating a case.
- Engineers gave up searching across systems and started relying on tribal knowledge. This caused us to spend additional time and energy trying to solve problems where the answers had already been discovered and documented.
- Backlogs grew and managers lacked visibility into early warning signs.
“We had over a dozen knowledge sources, and it was too messy for us to solve alone. We needed to unify them and make the best knowledge instantly accessible,” said Chris Romrell, Global Head of Technical Support, NICE CXone.
Unifying Knowledge Sources
Resolve SX pulls data from every knowledge repository into one clean, central experience. SupportLogic’s AI identifies the best-matching information and presents it directly within the case or the customer portal, complete with references and links.
“Resolve SX does the magic of deciding which source is best correlated and when to show results. It’s automation we simply couldn’t have built ourselves.”
Delivering Clear, Referenced Answers
Instead of giving customers a list of articles, Resolve SX generates a full, plain-language response with source links and supporting evidence. Search accuracy improved from 80 percent to 98 percent when information was available.
This experience is available everywhere NICE’s teams work:
- In the customer portal, improving customer’s search experience
- Integrated into the case creation workflow, reducing case creation
- Inside Salesforce Classic, providing the same generative search internally
- In Microsoft Teams, where engineers can mention SupportLogic AI to get a referenced answer instantly
Higher Case Deflection Through Improved Self-Service
Once Resolve SX was deployed in the portal, NICE saw a 4 to 5 percent monthly increase in case deflection, directly tied to improved answer accuracy and ease of use. Customers now receive answers before or while submitting a case, and can confirm whether the solution helped or if they need more assistance.
Creating a Living Knowledge Base
With an ever-evolving, Precision RAG-powered portal, NICE turns yesterday’s closed cases into knowledge that can deflect tomorrow’s tickets. Instead of static KCS articles that age quickly, each resolved case is ingested into SupportLogic’s LLM within 24 hours and becomes part of the searchable knowledge ecosystem.
“It’s a living knowledge base. The case we close today can deflect a case this afternoon.”
Automating Knowledge Creation
Through the Assist module, NICE now generates draft knowledge articles automatically from resolved cases. Support engineers or knowledge owners then review, validate, and publish those drafts, accelerating knowledge capture and ensuring accuracy.
“Assist lets us compare AI-generated drafts with existing content and decide whether to publish or merge. It’s a powerful way to scale accurate, living knowledge.”
Expanding Impact: From Portal to Teams
After deploying Resolve SX in the customer portal, NICE expanded to include internal knowledge sources and integrated SupportLogic into its internal workflows:
- Salesforce internal portal: Provides agents with the same generative search experience within Classic, returning summarized, referenced results across all sources.
- Microsoft Teams integration: Allows engineers to mention SupportLogic AI directly in chat and receive a generative, reference-linked answer – reducing the need to switch systems and accelerating resolution time.
This innovation is now extending benefits to NICE’s internal users, who generate 20–30% of total cases, and driving stronger collaboration with R&D.
The Broader Impact: From Support to Strategic Growth
NICE transformed how knowledge is used across the entire customer lifecycle. Engineers spend less time searching and more time solving meaningful problems. Managers use better insights to guide decisions, and customers get accurate answers faster than ever.
“AI helps us reimagine how support is done. We’re removing barriers for engineers, improving collaboration, and driving innovation across the organization. Now we can focus our people where they add the most value: on relationships, collaboration, and innovation.”
By moving from a “Search” model to a “Precision Answer” model, NICE isn’t just deflecting tickets; they are resolving issues at the point of interest.
NiCE attained 98% search accuracy with Knowledge Agent.
NICE partnered with SupportLogic to bring clarity, speed, and intelligence into how knowledge is created, discovered, and used across its support organization.
NiCE experienced a 4% in monthly case volume.
What Is Precision RAG?
Precision RAG (Retrieval-Augmented Generation) is a sophisticated AI architecture that solves the “hallucination” problem common in standard GenAI.
Unlike basic RAG, which often retrieves broad or irrelevant data, Precision RAG uses advanced semantic filtering and domain-specific anchors to pull only the most technically accurate information from a company’s unique knowledge base.
By grounding the AI in a “source of truth”—such as specific product documentation, past successful resolutions, and internal wikis—it ensures that the answers provided to support engineers and customers are not only fast but verified and contextually relevant. This allows NICE to automate complex troubleshooting with the confidence that the AI is providing high-fidelity, actionable solutions rather than generic guesses.
Precision RAG ensures that knowledge base queries do not simply return a “relevant document.” It instead ensures users receive the exact configuration step or code snippet needed for their specific issue. This reduces “bounce-backs” (where a deflected customer eventually opens a ticket anyway because the self-service answer was wrong) and drastically lowers the Mean Time to Resolution (MTTR) for the tickets that do reach the agents.
About NICE
NICE CXone delivers intelligent cloud solutions that help organizations create exceptional customer experiences. With more than 14,000 employees and a rapidly expanding customer base, NICE sought to evolve its global support model to keep pace with growth: improving resolution speed, accuracy, and self-service without expanding headcount.
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