San Francisco was buzzing last week, and Dreamforce 2025 made one thing crystal clear: the next era of enterprise is agentic. On the show floor, it was clear that more enterprises are finally realizing what we’ve known for years: data quality is what determines whether GenAI delivers promised ROI or falls short.
Our team spent three days on the floor having several impactful conversations, and the signal was loud. The Agentic Enterprise is here, but it lives or dies on the intelligence of your content.
Agentic AI is finally operational, not hypothetical
Agents were everywhere, from service workflows to sales cadences to back-office automations. The most compelling demos stitched context across systems, not just triggered actions.
Shelf’s take: agents cannot reason without context. If your content is fragmented, duplicative, or contradictory, your agents become confident underperformers. Shelf prepares content upstream so agents can understand intent, disambiguate answers, and act with precision across Agentforce, chatbots, and analytics tools.
Data quality is the GenAI bottleneck everyone admits, but few own
We heard the same refrain across enterprises of every size: garbage in, garbage out. Teams know their knowledge base is messy, but ownership is murky and fixes are manual.
Shelf’s take: this is not a dashboard problem, it is an upstream content intelligence problem. Shelf cleans, contextualizes, and structures unstructured content before it flows into Salesforce or Data Cloud, lifting AI accuracy, reducing rework, and shrinking risk at the source.
Upstream intelligence beats downstream cleanup
Several vendors are positioning around unstructured data, but most solutions operate downstream. They move and organize content after it has already fragmented across systems.
Shelf’s take: if you want reliable AI, you cannot mop the floor with the faucet still running. Shelf applies intelligence at ingestion. Think of it as a filter that enriches content with context, relationships, and policies before it reaches agents, search, or analytics. The result is less drift, higher answer quality, and fewer duct-taped fixes.
Retrieval is not accuracy, and structure is not meaning
There’s plenty of tools out there, like Glean, that improve retrieval. Platforms like Snowflake or Data Cloud handle structure. While these tools are exceptional at what they do, they don’t give unstructured content meaning.
Shelf’s take: accuracy comes from context, not just access. Shelf enriches documents with entities, intent, lineage, and trust signals so GenAI can reason, not guess. This is where leading integrators are leaning in. They see that content intelligence is the missing layer that makes the rest of the stack smarter.
Final thought
Dreamforce put a spotlight on the Agentic Enterprise, and the market is moving fast. The winners will not be the teams with the flashiest agent demo. They will be the teams that fix the upstream layer first, so every model, workflow, and agent runs on trusted, contextualized knowledge.
Shelf is purpose-built for this moment. If you are serious about operationalizing AI, start where outcomes are won or lost. Make your unstructured content intelligent before it hits Salesforce or anything downstream, and your agents will finally deliver the accuracy and scale you were promised. Talk to an expert.
