The problem
The internet makes people visible,
but not meaningfully discoverable.
LinkedIn reduces people to credentials.
Social platforms reduce them to performance.
Cold outreach leaves you guessing
who is relevant, why now, and what to say.
You type one sentence.
ohm. returns the people most relevant to that move.
"Find early-stage investors and design partners for an agentic introduction infrastructure platform."
AI Infrastructure Investor
Actively evaluates agentic infrastructure and consumer AI
Why it matters: Relevant for early fundraising and category feedback. Active in agentic infra this quarter.
Founder Community Operator
Runs high-density founder gatherings
Why it matters: Can validate ohm. as an event-based discovery layer.
Product Lead, Social AI
Memory, identity, AI-mediated interaction
Why it matters: Building adjacent workflows. Potential design partner.
No cold emails. No guessing. No wasted meetings.
Every connection comes with context, timing, and a reason to say yes.
From context to high-value conversations.
Connect context sources
Website, LinkedIn, writing, notes, email, calendar, or other sources you choose to share.
Generate a Portrait of Mind
ohm. builds an editable context profile of what you are working on, seeking, and ready for.
Define your next move
Describe the person, opportunity, or relationship you need next.
Search across networks
Your agent searches known and external networks. For people outside ohm., it uses public or user-approved context only.
Review high-fit matches
See recommended people with fit rationale, timing signals, mutual relevance, and risk of mismatch.
Act with a first-move strategy
ohm. recommends who to contact, why now, and how to begin the conversation.
Contextual fit analysis
ohm. is not matching profiles by keyword. It models both sides of a potential connection as structured context: intent, timing, relevance, constraints, and the likely value of a first conversation.
When both sides use ohm., agents evaluate fit directly. When a person is outside ohm., the system builds a limited contextual model from public or user-approved sources.
Haein J.
Building an agentic social infrastructure startup
Maya K.
GP at Sequoia, AI infrastructure focus
Resonance score
94/100
Context matching
Both agents share structured context and identify overlapping signal. Richer context than resumes or keywords.
Timing check
Are both sides actively seeking, available, and aligned on urgency? Bad timing kills good fits.
First move
If the fit passes, ohm. suggests who should reach out first, what to say, why now, and what to open.
Start with your context profile.
Upgrade when you are ready to search.
Create and edit your living context profile. Share it selectively. Receive limited inbound discovery.
Run intent-based searches, review high-fit people, simulate contextual fit, and get first-move recommendations.
ohm. exists because
The most powerful technology for changing a life was never artificial.
It was always another person.
Who are you trying to meet next?
