Community builders & super-connectors

See how you'd use Dhaga

Meet Maya Okonkwo, a demo contact in a community-builder's Dhaga account. She's the founder of Thermrail, a super-connector member who walks into a meetup already knowing half the room and leaves having made five introductions for other people.

It remembers what you'd forget. Maya's profile holds the facts that make her matter: she's building a climate-hardware startup, she's ex-Tesla on the hardware side, she runs a monthly hardware dinner, and — the fact you'd never want to lose — she loves making intros and is actively asking to meet more hardware founders. It also holds who she should meet (Naomi Okafor at Solverra, Helena Voss for a seed conversation, Theo Lindgren at Voltrail), that you last reached out 45 days ago against a 30-day cadence so she's overdue, and who she's linked to: introduced to Naomi, brought into the community by Helena, mentoring Lucia Ferrari and Devon Clarke, and old friends with Iris Kowalski. Every fact keeps a receipt back to the note it came from.

Every morning, it tells you who to reconnect with. The daily view surfaces the members who've gone quiet — Maya among them, past her cadence — alongside the open follow-ups you actually owe people: introduce Maya to the Solverra founder this week, and invite her to speak at the spring series this month. Each item is tied to a real member, so the list is a to-do, not a feed.

"Who should meet whom," made visible. Focus the graph on Maya and the connective tissue you hold in your head shows up as labeled edges: who introduced her, who she was introduced to, who she works with, and the two members she mentors. Layered on top are the events you met at — the March, April and May meetups, ThreadCon, and the founders' dinners — so a member's whole history sits on one canvas.

There's a specific kind of person every scene has one of. The one who, when you describe a problem, says "oh, you need to talk to Devin" — and they're right, and Devin changes your year. They run the meetup, host the dinner, keep the Slack alive. Their superpower isn't charisma. It's memory: a living map of who does what, who's looking for whom, and who two people would click if only they met.

That map is astonishingly valuable and almost impossible to hold in your head past a certain size. This is the gap Dhaga is built to close.

The event firehose: dozens of new people in one night

An event is a paradox. It's where you meet the most people and where you retain the least about any of them. You have forty good thirty-second conversations, and by the parking lot half have already blurred into "the one who did something with supply chains, I think."

Dhaga is built for capture at exactly that moment. At the badge table or mid-room, scan a business card or event badge — the fastest way to log someone when your hands are full and the line is moving. Stepping out for air, record a voice note while the conversation is still warm: "Maya, just left a climate fund, wants to angel-invest in hardware, knows Devin from grad school, looking for a technical co-founder." Back at your desk, web quick-add or the browser extension catches the LinkedIn tabs you left open, and a CSV or attendee-list import brings a whole roster in at once.

The point isn't a tidy contact list. It's that three weeks later, when someone asks "do you know any climate-hardware angels?", Maya surfaces — with the reason she's a fit attached, in your own words.

The graph is the connector's real asset

A flat list of contacts tells you who you know. It can't tell you who should meet whom — and that's the entire job. Dhaga turns your notes into a private knowledge graph: not just people, but the structured facts and relationships between them. Who knows whom. Who shares an interest. Who was at which event. Who you already introduced to whom.

This is the difference between a filing cabinet and a mental model you can actually query. When Maya mentions she knows Devin, that becomes an edge in the graph, not a sentence you'll forget. When three separate people over three months tell you they're into "climate + hardware," Dhaga holds them as a cluster you can find on demand — instead of you half-remembering that "a couple of people" were into that.

For a super-connector, the graph is the value. Every good introduction you've ever made was a small act of graph traversal you did in your head. Dhaga makes that traversal something you can do across a thousand people instead of the few dozen you can keep loaded at once.

"Who should these two people meet?"

The highest-leverage thing a connector does is say "you two should talk" — and be right. Dhaga's recall works in plain English, answered only from your own notes, so it never invents a connection you didn't actually observe.

Ask it the questions a connector actually asks:

• "Who in my network is into climate and hardware?"
• "Who should I introduce to the founder I just met who's raising a pre-seed?"
• "Which of my people are hiring senior designers right now?"
• "Who do I know that's mentioned wanting to break into fintech?"

That last mile — "who should meet whom" — is where a connector earns their reputation, and where memory fails first at scale. Dhaga lets you stand in a room, meet someone new, and immediately think across your entire network for the two or three people they genuinely need to know, instead of only the handful you can recall on the spot.

And every AI-derived fact keeps a receipt back to the note it came from. When Dhaga suggests Maya and Devin should reconnect, you can see the conversation it learned that from — your own words, dated. Your intros land because they're built on something real, not a hallucinated hunch. That's what makes you the person whose introductions are always worth taking.

Remembering member context — at community scale

Warmth doesn't scale by trying harder. The member who told you six months ago that they'd just had a kid, switched jobs, and were nervous about public speaking deserves to be remembered as that person — not greeted as a stranger because your memory ran out of room.

Because Dhaga structures each note into facts on a person's profile, that context compounds instead of evaporating. The next time you see them, a quick look tells you what's going on in their world: the new role, the side project, the intro you promised and haven't made yet. Multiply that across a community and you become the organizer who somehow remembers everyone — because you have a system that does.

Recall also catches the people slipping away. "Who haven't I talked to since the spring event?" is the question that keeps a community warm, and it's exactly the one no human tracks reliably across hundreds of members. The graph knows the last time you touched each person, so the threads fraying at the edges get your attention before they snap.

Staying ahead of your people, without the noise

Some of your members you especially want to stay ahead of — the ones whose next move is worth being early to. Dhaga's proactive intelligence is an opt-in watchlist: you pick that focused set, and Dhaga watches for meaningful changes, like a new role or company. It's deliberately bounded — you choose who's on it, and it's a short list, not a firehose across your whole community. When someone moves, that's a reason to reach out with something real, and often a reason to make a fresh introduction.

Around each touch, Dhaga can help you show up prepared. A pre-meeting brief pulls together what you already know before a coffee, so you walk in remembering the side project and the kid's name. User-triggered enrichment and follow-up draft assistance help you move faster on the promised intro — always on your command, never firing on its own or scraping in the background.

Your community is yours — keep it that way

For a community builder, the network of relationships you've cultivated is the thing you've built. Handing it to a platform that can change terms, lock you in, or quietly mine it is a risk to the community itself.

Dhaga is privacy-first and self-hostable. Run it yourself, bring your own AI API key so your members' details never fund someone else's model business, and export everything at any time. There's no enrichment happening quietly in the background and no silent data collection — the AI acts when you ask it to. The trust your community places in you stays intact, and the map you built stays under your control.

The thread between everyone

Being the connective tissue for hundreds of people was never about knowing them all at once. It's about being able to reach the right thread at the right moment — to look at a new founder and instantly know the three people they should meet. Dhaga is the memory that makes that possible past the point where your own runs out, so your intros stay on-point and your community stays warm as it grows.

If you're curious how a network this size holds together under the hood, the engineering blog walks through rendering a 21,000-node graph — a fitting read for anyone who is the center of one.

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