When everything happens inside one large conversation, that conversation gradually accumulates unrelated topics: client questions, market research, workflow setup, document analysis, and product support.
Over time, the conversation history becomes diluted. When the AI generates a response, it must interpret a large amount of mixed context.
Chat threads solve this problem.
Each chat thread maintains its own conversation history and focus. This allows Vega to reason within a clearer context, which increases the likelihood of generating more precise and relevant outputs.
In practice, this means you can maintain separate chat threads for:
a specific client
a document analysis
a research topic
a workflow you are building
Each chat thread becomes a focused workspace for that topic.
Chat threads in Vega
This Help Center article focuses on chat threads in the Vega chat, but the same concept also applies to the Vega Outlook plugin and the Vega Gmail assistant.
In those environments, each email conversation you open in your inbox already functions as a thread in Vega. When you interact with Vega in that email conversation, Vega uses the email thread as the context for the discussion.
The Vega chat
The Vega chat in the web platform allows you to create and manage multiple chat threads.
Each chat thread represents a focused conversation with Vega. You can return to a chat thread at any time and continue the discussion with the existing context already available.
This is particularly useful when working through multi-step tasks such as:
analyzing client documents
preparing a financial analysis
researching a planning topic
building CRM records from a conversation
Instead of restarting the context each time, the chat thread keeps the conversation organized.
You can create a new chat thread by clicking New at the top right of the Vega chat.
Push to Talk (PTT)
Vega also supports Push to Talk (PTT), which allows you to dictate your message instead of typing it.
Simply press and hold the space bar on your keyboard to start dictation.
This feature is designed to make conversations with Vega faster and more natural, especially when you want to ask longer questions or explain context in detail.
And the Push to Talk interface also comes with a pretty cool design!
Anywhere in Vega
You can open the Vega chat from anywhere in the platform.
You can open it in two ways:
1. Click the AI icon in the top right of your screen
This will open the latest chat thread you were using from the home page of the Vega web platform.
2. Click the (+) icon and select “New chat.”
This will open a new chat thread. If you are on a page such as a meeting page and clients are linked to that meeting, Vega will automatically link those clients to the chat thread.
When you open a chat thread from somewhere outside the dedicated Vega chat (for example from another page in Vega), Vega is aware of the page you are currently on. This context helps Vega interpret your request.
Features of the Vega chat and threads
Chat threads are not only about organizing conversations. They also allow you to interact with several Vega capabilities directly from the chat.
Link a client to a chat thread
Chats can be connected to contacts, which allows Vega to understand who the conversation is about.
There are two ways this happens.
Automatically
If you ask a question and mention a client name or household directly in your query, Vega will automatically link that contact or household to the chat thread.
For example:
“What did we discuss with Mark Pace during the last meeting?”
Once that link is established, the chat is now associated with that client or household.
From that point forward, you do not need to repeat the full name in future messages within that same chat. Vega already understands the context.
Manually
You can also link a contact or household manually to a chat before asking your question.
In that case, you can ask your question more naturally without specifying the full client name, since the context is already defined.
This is especially useful when:
you are working on a client over multiple steps
you want to avoid repeating identifiers in each message
you are preparing or analyzing information tied to a specific household
In both cases, the result is the same: the chat thread becomes a client-specific workspace.
Sharing chat threads
Chat threads are where many workflows start in Vega.
You might use a chat thread to:
analyze a client situation
research a planning question
prepare for a meeting
create tasks or notes
work through a multi-step project
When that conversation becomes useful for someone else on your team, you can share the entire thread instead of copying messages back and forth.
To share a chat thread:
Open the chat thread you want to share
Click the (+) button at the bottom left of the chat
Select Chat settings
Choose who should have access
From there, you can share the thread with:
specific users
teams
your entire firm
Once shared, other users can access the same conversation and continue working with the existing context.
This means they do not need to restart from scratch or ask Vega to recreate the same analysis again.
AI agents
When you interact with Vega in a chat thread, different AI agents may be activated depending on the request.
These agents allow Vega to retrieve and reason across different types of information, including:
Contacts
The Contacts agent retrieves client and prospect information from your CRM and past interactions. Vega can search across emails, notes, tasks, contact profiles, meetings, and transcripts.
Economic data
This agent retrieves macroeconomic information such as inflation, interest rates, employment data, GDP, and other indicators that influence financial planning.
Market data
This agent provides insights on markets, including asset class behavior, trends, historical performance, and market structure.
Web
The Web agent retrieves external information such as financial publications, regulatory content, and current news. It also activates specialized sources like IRS data for tax rules and contribution limits.
Firm data
This agent retrieves information stored about your firm, including processes, templates, preferences, and internal knowledge.
Support
The Support agent helps answer questions about Vega and can guide you on features, configuration, and troubleshooting.
For a deeper explanation of how AI agents work in Vega, see this Help Center article.
Analyze documents
You can attach files directly to a chat thread by clicking the paperclip icon at the bottom right of the Vega chat, next to the send button.
Vega can process and analyze those files as part of the conversation. This includes tasks such as:
summarizing documents
extracting key information
comparing multiple files
answering questions about a document
Common examples include tax returns, portfolio reports, and other financial documents.
Instant vs Thinking
At the bottom of the Vega chat, just below the message area, you can choose between Instant and Thinking.
Instant is the default mode. It is designed for speed and works well for most day-to-day questions, retrieval requests, and quick back-and-forth conversations.
You can also switch to Thinking when you want Vega to spend more time reasoning before responding. This mode is better suited for requests that require deeper analysis, more synthesis, or more careful interpretation.
Creation of objects
You can also ask Vega to create objects directly from the chat.
Depending on your setup, Vega can generate and prepare records such as:
notes
tasks
client profiles
appointments
other system objects
These objects can then be reviewed and synced to your CRM, or stored directly in Vega if you are not using a CRM with Vega.
For example, you could tell Vega:
“Create a note for Ben Lewis that he is traveling to Spain in two weeks, and create a task to reach out to him when he returns during the first week of April.”
Chat list and ordering
Your chat list is organized in chronological order based on the most recent activity.
This means:
when a chat is updated, it moves to the top of your list
when you return to an older chat and continue the conversation, it becomes your most recent working context
This allows your most active workstreams to naturally stay at the top without requiring manual organization.
Pinning chats
You also have the ability to pin chats in Vega.
Pinning allows you to keep important chats readily accessible, regardless of when they were last updated.
This is useful for:
ongoing client work
internal workflows
recurring research topics
support or implementation threads
Pinned chat threads remain at the top of your thread list, giving you quick access to the conversations that matter most.
In the Activity view
Once a chat is linked to a contact or household, it becomes part of that client’s activity history.
When you navigate to a contact or household page in Vega and open the Activity section, you will see:
notes
meetings
emails
tasks
and also chat threads where that client is linked
This means that chats are not isolated conversations. They are part of the full relationship history.
Over time, this allows you to:
revisit prior discussions
understand context behind decisions
track how thinking and planning evolved
Chats effectively become another source of structured client knowledge.
Example of using a chat thread end-to-end
Here is a practical example of how a chat thread can be used as a complete workflow:
You upload a client’s tax return into a chat thread and ask Vega to analyze it.
You go back and forth with Vega to retrieve specific information, clarify certain items, and interpret the relevant details.
Once the analysis is complete, the chat thread now contains a structured discussion about that client’s financial information.
At that point, you can ask Vega to create a note summarizing the key takeaways from the conversation, and Vega can prepare that note for your CRM directly from the chat.
The chat thread therefore becomes both a working conversation and a source of structured information that can feed into your systems.
A practical way to think about it
Chats are where conversations happen.
Linking connects those conversations to your clients.
The activity view ensures those conversations are not lost, but instead become part of the client history.
Pinning helps you stay organized around your most important work.
Together, these elements turn chat threads into more than just AI conversations. They become structured, contextual workspaces tied directly to your client relationships.