Delivering AI for B2B: Trust and Accuracy are Paramount
We are all reading the headlines from the large LLM providers about the leaps in model capabilities. The bleeding edge is exciting. Similarly, there’s noise from legacy SaaS providers about the promises of their to-be-delivered agents. Performance, costs, and trustworthiness for scalable B2B deployments, off the shelf? Not so ready yet.
The practical reality inside medium and large enterprises is that customer-facing AI solutions are still in their infancy in terms of adoption. Knowledgebases are still accessed via search and endless lists of articles. Enablement systems, ticketing systems, and CRM systems are myopically focused on generating outputs from content they already house.
And, what we’re seeing is that – despite all the marketing dollars being spent by legacy SaaS players – actually delivering accurate and trustworthy answers on a consistent basis is really quite difficult.
A Multi-Layered Approach to Delivering a Customer-Facing AI Platform
Conceptually, the idea of a customer asking a “How do I?” product support question and an LLM delivering the answer is quite simple. But the reality is that, to do this consistently and at a level acceptable by enterprise class customers requires a multi-layered approach to creating an enterprise-ready “answer pipeline” based on Retrieval-Augmented Generation, or RAG.
Embrace offers a set of product capabilities that ensure our customers achieve accurate outputs. First, we ensure you can draw from the most relevant product knowledge content regardless of where it may live. Embrace offers pre-built integrations to sources like Zendesk Guide, Confluence, Notion, Guru, and others, making it easy to draw from your library of product content, typically from multiple places simultaneously.
Embrace provides the ability to add content from websites, files, and integrations.
Additionally, our Insights dashboard puts a spotlight on the common topics that are emerging and need attention. We highlight spots where there may not be underlying content to support an answer or places where user feedback highlights concerns.
Embrace creates AI-generated topics from support interactions, including ‘Topics that need attention’
We also make it easy to address knowledge gaps. A knowledge manager can quickly add an existing document into a content collection. Embrace can also help draft a new knowledgebase article or a subject matter expert can record themselves speaking to enhance content.
Together, these product capabilities help create a virtuous cycle that improves accuracy.
Beyond Simple RAG: AI-Driven Knowledge Pipelines
We’ve invested heavily in our underlying technology platform, including taking a multi-layered approach to the RAG pipeline in order to deliver a level of consistency, accuracy, and trustworthiness that is required – at a minimum – for a successful enterprise deployment of AI-powered, agentic product support. The three layers are built to handle the core problems inherent in B2B product support, enablement, training, and education:
Layer #1 – Preparing Enterprise Content for AI: Ingestion
It’s one thing to ingest a simple five page, well-formatted word document for RAG and answer a question. It’s another thing to handle hundred page technical manuals laden with images and dense tables, thousands of support ticket conversations, or endless pages of dense training content. 100% of Embrace’s customers have the problem of large scale, diverse, multi-modal content – ingesting, enriching, and preparing that content requires proprietary investments across the ingestion pipeline.
Layer #2 – Accuracy and Consistency: Retrieval
Delivering accurate answers, consistently, across a vast amount of content, much of which gets updated (and/or outdated) over time is a core requirement of B2B support. Inevitably, there are sources with very similar sounding content and depending on the specific question, one may be more appropriate than another. The right answer depends on understanding the context of the question and the content, and it may require a ‘translation layer’ between company jargon and customer language. The answer may be best delivered by an image or the text that describes the image. Embrace has built a layer that deeply understands the question and aligns the content and context to deliver consistently accurate answers.
Layer #3 – Understanding Context, Building Trust: Generation
It’s one thing to deliver an answer, it’s another to trust that the system won’t hallucinate, will reference provided sources and, will follow agent instructions. It’s also key to provide control to the enterprise for everything from tone and voice, to disclaimers and complying with key legal language. Testing, visibility, insights and managing constraints are foundational to an enterprise AI platform that delivers trust as part of the solution.
Embrace’s Partnership With Customers During Implementation
Embrace’s commitment to customer success is evident in its partnership approach during implementation and is a hallmark of our business. Our success is your success. We aim for a rapid implementation and one that is designed to deliver highly accurate and trustworthy outputs. We help our customers spot knowledge gaps as well as partner in the creation of AI Agents that deliver the most accurate and effective results. We take a hands-on and highly communicative approach that leads to both rapid ROI and highly accurate outputs from our solution.
“With Embrace, we went from a discussion around the art of the possible to doing something that added vlaue in a remarkably short period of time.”
Chris Cox
Chief Technology & Digital Officer, Keller Williams
Conclusion
Embrace is a powerful tool for B2B support leaders looking to enhance their product support capabilities. With its advanced product and technology features, Embrace delivers accurate and trustworthy outputs that you can rely on. The platform’s strong customer partnerships ensure that it meets your specific needs, providing a seamless and efficient implementation process.
By choosing Embrace, you are choosing a platform you can trust.
