Asking Questions with Chat

The Chat tab lets you ask natural language questions across your entire knowledge base. Instead of browsing and filtering manually, just ask what you want to know and get an AI-powered answer grounded in your actual data.

Starting a conversation

Open the Chat tab and type your question in the message box. There is no special syntax required -- write the way you would ask a colleague. Hit send, and Upstream searches your knowledge base, finds the most relevant entities, and generates an answer.

Multi-turn conversations

Chat preserves context across messages. You can ask a question, then follow up with clarifications or dig deeper without repeating yourself. For example:

"What are the top objections we hear from enterprise prospects?"
"Which of those come up most in deals over $100K?"
"Do we have any messaging themes that address the security objection?"

Each follow-up builds on the previous exchange, so the conversation stays focused and productive.

Citations

Every answer includes numbered references like [1], [2], [3] that link back to the specific entities in your knowledge base. Click a citation to see the full source entity, including its confidence score, relationships, and the original document it came from. Citations let you verify answers and trace insights back to their origin.

Tool use during conversation

The AI can do more than answer questions. During a conversation, it can:

Create artifacts -- Ask it to generate a battle card, account brief, or summary and it will build one from your knowledge base right in the conversation.
Propose new entities -- If the AI identifies an insight worth capturing, it can suggest adding it as a new entity to your knowledge base.
Search your knowledge -- The AI actively searches your entities, relationships, and documents to find the best answer. You will see when it pulls in relevant context.

Example questions by role

Sales:

"What objections do prospects mention most about our pricing?"
"Give me a quick account brief for Acme Corp before my call tomorrow."
"What pain points do mid-market companies mention compared to enterprise?"

Marketing:

"What messaging themes resonate with technical buyers?"
"What content ideas have we captured from customer feedback this quarter?"
"How do prospects describe our product compared to Competitor X?"

Product:

"What are the most requested features from enterprise customers?"
"Are there any process gaps that multiple customers have mentioned?"
"What customer feedback have we received about the onboarding experience?"

RevOps:

"What deal context patterns appear in deals that closed this quarter?"
"Are there common objections in deals that stalled?"
"What market insights have we captured about our target segments?"

Tips for getting better answers

Be specific. "What objections do enterprise prospects raise about security?" will give you a more focused answer than "What are our objections?"
Reference timeframes. "What feature requests came in this quarter?" narrows the scope and gives you more relevant results.
Ask follow-ups. If the first answer is too broad, ask a more targeted follow-up. The AI remembers the full conversation.
Name what you need. If you want a summary, a list, or a comparison, say so. "Compare the top three competitor mentions by frequency" tells the AI exactly what format you expect.
Use entity types. Mentioning types like "pain points," "objections," or "messaging themes" helps the AI focus on the right part of your knowledge base.

Using the Knowledge Browser -- Browse the entities that power chat answers
Creating Artifacts -- Generate deliverables directly from chat
Using the Canvas Workspace -- Organize ideas visually after a chat session

Still need help?

Email us at hello@getupstream.ai -- we read every message.