Excerpt: Aura Search helps GTM teams get fast, cited answers from trusted Seismic content. Learn how it works, when to use it, and how it helps sellers, marketers, and enablement teams move faster.
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It’s 8:43 a.m., and a seller has 17 minutes before a discovery call with a healthcare prospect. They’ve read the account notes and remember there’s a new pitch deck somewhere – but in their organization, “somewhere” can be any number of places.
They open one folder, then another. They search for “healthcare deck” and get six results, two of which look nearly identical. They wonder which one is approved or if the competitive messaging is up to date. With every second, they’re slightly closer to their 9 a.m. meeting.
These are exactly the moments Aura Search is built for.
Instead of searching by folder, file name, or memory, a seller can ask a question in plain language: “What should I cover in a discovery call about Product X for a healthcare client?” Aura Search can return a concise answer grounded in trusted Seismic content, show the sources behind that answer, and help the rep move from “I think this is right” to “I know where this came from.”
What is Aura Search?
Aura Search is Seismic’s AI-powered generative search capability. It helps users ask natural-language questions and receive answers grounded in the trusted content inside their Seismic environment. Instead of only showing a ranked list of documents, Aura Search can generate a conversational answer, include citations, and surface the source content used to create that answer.
Think of it as a smarter way to search for sales and enablement knowledge. A standard search might return a list of files that contain the words “pricing,” “objections,” or “healthcare.” Aura Search goes a step further by trying to understand what the user wants to accomplish. Are they looking for an answer, a document, or an existing Digital Sales Room? Aura Search analyzes intent, retrieves relevant information, and returns an answer that can be traced back to specific Seismic content.
That traceability is important. For GTM teams, speed is only valuable when it comes with confidence. Sellers need to know that the answer they’re using is approved, current, relevant, and appropriate for the buyer conversation in front of them. Aura Search is designed to help users move quickly without leaving trust behind.
Why Aura Search matters for GTM teams
Most teams have more than enough content but, oftentimes, the challenge is making the right content easy to find when people need it.
When information is hard to find, productivity takes a hit. Seismic’s 2023 Value of Enablement Report found that respondents without enablement technology spend an average of 10 hours per week tracking down, comparing, or revising content. The same report found that 54% said the content they use is not easily accessible, and 51% said they have misspoken during a sales or customer call while trying to locate content or information.
Aura Search helps address that problem by giving teams a more direct path to answers. Most generative search capabilities allow users to ask where a deck is. Aura Search goes a step further, allowing users to ask more pointed, context-driven questions such as, “Do we have a relevant proof point for this industry?” or “Help me get ready for this conversation.”
How Aura Search works
Aura Search blends traditional search techniques with AI to understand the user’s prompt, retrieve relevant content, and generate a sourced response. At a high level, Aura Search follows a straightforward process: it interprets a user's question, retrieves the most relevant information from trusted Seismic content, and generates a response grounded in those sources. Throughout the process, it respects existing permissions and security controls.
Here’s what that means in plain English.
1. Aura Search interprets the prompt
A user can type a natural-language question, such as “What are the top objections to Product X?” or “What should I include in a follow-up email for a retail CMO?” Aura Search analyzes the prompt to understand the user’s intent, keywords, freshness indicators, and desired output.
That last part matters because “Find a pitch deck” and “Write a prospecting email using our latest pitch deck” are not the same request. Aura Search is designed to recognize the difference so it can return a more useful result.
2. Aura Search retrieves relevant information
Aura Search uses a hybrid retrieval approach. It can perform lexical matching, which looks for keyword-based matches across areas like titles, body text, custom properties, and related metadata. It can also perform semantic matching, which helps identify conceptually relevant content even when the wording doesn’t match exactly. It can apply filters, freshness, and re-rank matched snippets based on retrieval score and semantic similarity.
That means a seller doesn’t need to know the exact title of the deck, the exact phrase marketing used, or the exact folder where a customer story lives. They can ask the way they’d ask a teammate.
3. Aura Search respects permissions and business rules
Aura Search is built to use the content a user is allowed to access. It enforces business rules, including user permissions and allowed content types.
For enterprise GTM teams, this is a big deal. AI-generated answers are only useful if they follow the same governance expectations as the rest of the enablement workflow. Sellers need speed, but sales, marketing, enablement, legal, and compliance teams also need control.
4. Aura Search generates an answer with citations
Once Aura Search retrieves the most relevant passages and document metadata, it sends that information to a large language model to generate a natural-language answer. The Aura documentation notes that the answer is grounded only in the provided document metadata and passages, and it returns relevant citations.
The citations help users review where the answer came from. That makes the response easier to trust, easier to verify, and easier to turn into action.
5. Aura Search helps users act on what they find
Search is only useful if it helps someone do the next thing. Aura responses and sources can be used as the basis for LiveSend email and digital sales room creation. For example, a user can prompt Aura to draft an email and then share the relevant content item, with Aura’s suggested email text populating the LiveSend email workflow.
Aura Search vs. traditional search
Traditional search is useful when you know what you’re looking for. You type a term, review a list of results, open a few files, and decide which one fits. That workflow works well for known-item discovery: “Find the Q4 pricing deck,” “Find the onboarding checklist,” or “Find the Product X case study.”
Aura Search is more useful when the user has a question, a task, or a decision to make. Instead of only returning a list of files, Aura can return a summary answer with numbered citations and a list of sources.
That's important to note because Aura Search responds differently based on the type of query. When a user enters a question in the search bar, Aura can display an answer panel with a summary and sources. When a user enters keywords or search terms rather than a question, Aura displays search results without the answer panel because those queries signal that the user likely wants to find specific content. That gives users the best of both worlds: classic search when they want a document, generative search when they want an answer.
Aura Search vs. Aura Chat
Aura Search and Aura Chat work together, but they’re not the same experience.
Aura Search is best for quick, intent-driven answers. A seller asks a question, Aura searches trusted content, and the seller gets a cited response. It’s ideal when the user needs to find an answer, locate content, or get moving quickly.
Aura Chat takes that experience further with multi-turn conversation. It keeps context from earlier questions, which lets users clarify, refine, and explore. For example, a user might start with “Give me a summary of Product X,” then ask, “Now tailor it for a CMO in retail,” and then follow with, “Turn it into a sales email.” The documentation describes Aura Chat as a deeper, multi-turn experience for exploration, follow-up questions, and decision-making.
In practice, Aura Search helps users start fast, while Aura Chat helps them keep going.
How to use Aura Search
Aura Search can be used from several places in Seismic, depending on the user’s workflow.
Search from the global search bar
Users can enter a search term or natural-language question in the main Seismic search bar. If the query is question-based, Aura displays an answer and sources. If the query is keyword-based, Aura displays search results. Users can then review the answer, inspect sources, copy the response, rate the answer, and continue the conversation in the Aura Chat panel.
Search and chat from the Aura panel
Users can open the Aura panel from the sparkle icon in Seismic. The panel includes starter prompts such as Find, Write, Learn, and Summarize. Users can review sources, preview content, remove a source, copy an answer, and share content through workflows such as digital sales rooms, LiveSend emails, or bulk emails, depending on company configuration.
Search from the browser extension
Aura generative search is available in the Seismic browser extension for Chrome and Edge. The browser extension supports single-turn search, but it does not include follow-up chat capabilities. That’s helpful for sellers who need quick answers while working outside the main Seismic web experience.
Ask questions within DocCenter or Collections content
Users can also ask questions about specific content items in DocCenter or Collections. This helps users quickly summarize a document, identify key points, or answer detailed questions directly from the content. When using generative search on a Page content item, Aura searches linked content items, as well as the text on the Page itself.
Aura Search use cases
Aura Search can support several GTM workflows, from seller prep to enablement planning.
Meeting preparation
A seller can ask Aura Search what to cover in a discovery call, how to position a product for a specific industry, or which case studies are relevant for a certain persona. Instead of building a talk track from memory, they can ground their prep in approved content.
Example prompts:
- “What should I cover in a discovery call about [Product] for a healthcare client?”
- “What are the top objections to [Product], and how should I respond?”
- “Do we have a case study for financial services clients in EMEA?”
Content discovery
Aura Search can help sellers find the right deck, one-pager, case study, talk track, or competitive resource without needing to know the exact title. That’s especially useful when content libraries are large, products change quickly, or multiple teams publish assets.
Example prompts:
- “Find a pitch deck for [Product].”
- “Which assets are approved for external sharing with retail buyers?”
- “Show me recent content about [Competitor].”
Messaging refinement
Sellers can use Aura Search and Aura Chat to turn sourced content into a more usable message. For example, they might ask Aura for a 30-second pitch, then ask for a more casual LinkedIn version, then ask for a follow-up email with a LiveSend link.
This workflow helps sellers tailor messages without starting from a blank page.
Enablement content creation
Enablement teams can use Aura Search to gather common questions, objections, product differentiators, or vertical-specific insights. From there, they can create FAQs, one-pagers, training materials, or sales play content.
Example prompts:
- “What are the top questions new reps have about [Product]?”
- “Turn this into an FAQ with headings.”
- “What are the key differentiators for [Product] in healthcare and financial services?”
Sales follow-up
A seller can ask Aura to draft a follow-up email based on a sourced answer and relevant content. Aura can then help move the response into a share workflow like LiveSend or a digital sales room, depending on configuration. That keeps momentum going after the meeting. And in sales, momentum is kind of the whole game.
Best practices for better Aura Search results
Aura Search understands natural language, so users don’t need to write perfect prompts. Still, better prompts lead to better answers.
Be specific when the answer needs to be specific. “What are Q3 sales trends for healthcare in North America?” is more useful than “Q3 sales trends.” Add details such as product, industry, persona, region, buyer stage, and timeframe.
Use clear action verbs. Aura can better understand what the user wants when prompts include verbs such as summarize, compare, explain, write, find, tailor, or turn into. We recommend intent-based verbs because Aura understands commands like summarize, compare, explain, and write.
Ask follow-up questions. Start broad, then narrow the response. A seller might begin with a product summary, then ask Aura to tailor it for a retail CMO, then ask Aura to turn it into a prospecting email.
Use filters when needed. Users can restrict responses to certain tagged content. Filters can be applied so Aura’s responses are restricted to selected tagged content.
Review the sources. Cited answers are one of Aura Search’s biggest strengths. Users can inspect the source content, preview documents, and open the original content in Seismic.
Keep content healthy. Generative answers are only as good as the assets they draw from. Aura may return incorrect answers if it draws from outdated or inaccurate content, or documents that conflict with one another.
What to look for in an AI-powered search solution
Not all AI-powered search tools are designed for go-to-market teams. While general-purpose AI can generate text, it doesn't necessarily know which content is approved, which assets a seller is allowed to access, or how to connect answers to the workflows that drive revenue.
The most effective AI search solutions should help teams find trusted answers, act on them with confidence, and stay aligned with company strategy.
Look for a solution that grounds every response in approved content and provides citations so users can verify where information came from. Enterprise-grade security and permissions are equally important, ensuring every answer reflects the same governance policies that protect the rest of your content library.
Finally, AI search should fit naturally into the way teams already work. Whether a seller is preparing for a meeting, drafting a follow-up email, or sharing content through a digital sales room, search should help them move seamlessly from finding information to taking action. Aura Search does exactly that by combining trusted, cited answers with native Seismic workflows across the web application and browser extension, helping GTM teams spend less time searching and more time engaging buyers.
