Deep Search searches across your contacts, interactions, notes, email threads, and companies simultaneously. Results are ranked by a combination of semantic relevance and how recently you’ve interacted with that person.
Regular search vs. Deep Search
Orbis has two ways to search your data:| Regular search | Deep Search | |
|---|---|---|
| How it works | Matches exact names, emails, and company names | Understands the meaning of your query |
| Good for | Finding a specific person you can name | Finding people based on context or relationship |
| Example | ”Sarah Chen" | "investors I haven’t spoken to in a while” |
⌘K or Ctrl+K). Deep Search is accessed through the search bar in the sidebar or via the Deep Search section.
How to use Deep Search
Open Deep Search
Click the Deep Search icon in the left sidebar, or use the search bar at the top of the page.
Type your query
Enter a natural language question or description. You don’t need special syntax — write it the way you’d say it out loud.
Review results
Results appear across tabs: contacts, interactions, notes, threads, and companies. Each result shows a relevance score and a snippet of why it matched.
Example queries
These are the kinds of queries Deep Search handles well:Relationship timing
“investors I haven’t talked to in 3 months”
Location and industry
“contacts who work in fintech in New York”
Meeting context
“people I met at conferences”
Follow-up needs
“who do I need to follow up with this week”
Role or seniority
“CTOs and VPs of Engineering in my network”
Company type
“founders at Series A startups”
- “emails about fundraising from last quarter”
- “contacts at companies that do enterprise SaaS”
- “people I emailed last week but haven’t responded to”
- “notes I wrote after calls with investors”
- “anyone who works in climate tech or clean energy”
How results are ranked
Deep Search ranks results using two signals:- Semantic similarity — how closely the contact’s profile, notes, and interaction history match the meaning of your query
- Interaction recency — contacts you’ve communicated with more recently are weighted higher
Search modes
When you submit a query, Deep Search automatically detects what you’re looking for:- Searching your network — if your query uses relationship language (“talked to”, “emailed”, “follow up”), Deep Search looks through your existing contacts and interactions
- Discovering new people — if your query uses discovery language (“find investors in”, “who are the top VPs at”), Deep Search can also surface people outside your existing contacts
AI chat interface
Deep Search includes a full conversational interface. You can ask follow-up questions, refine results, and even take actions: Finding and saving information:- “Search for Stripe and create a note about what they do”
- “Find contacts at OpenAI and show me my last interaction with each of them”
- “Create a contact for Jane Smith, VP Engineering at Acme Corp, jane@acme.com”
- “Save a note summarizing my call with the Sequoia team”
- “Who are the investors in my network that focus on B2B SaaS? Show me my interaction history with each one.”
Attaching files
You can attach files to your Deep Search messages. The AI reads the content and incorporates it into its response — useful for pasting in a meeting transcript, pitch deck, or CSV and asking questions about it.Deep Research mode
For complex, multi-step analysis, you can enable Deep Research mode. This uses a more powerful reasoning model that can spend more time analyzing your query before responding. It’s slower but better for questions like:- “Summarize the state of my relationships with climate tech investors and suggest who I should prioritize reconnecting with”
- “Analyze all my interactions with the Andreessen Horowitz team over the last year”