01 · Capture
Scan anything in five seconds.
Card, badge, QR, or a LinkedIn page — one photo, read by AI in seconds. The contact is structured before the handshake ends.
Features
Keep the context. Find the connection. Make the next move.
Dhaga turns everyday professional interactions into a private, searchable memory—without making you maintain another spreadsheet.
You met 47 people at your last conference. You'll remember 3.
A familiar story, not a stat we collected — picture your last conference.
47
people you met at your last conference
5
you actually followed up with
3
you'll remember by next quarter
How it works
From handshake to knowledge graph in three moves.
STEP 1
Capture in five seconds
Card, badge, QR, a LinkedIn page, a pasted email, or a contact forwarded to WhatsApp or Telegram — or just talk. Voice transcription runs on-device, free; photos get a fast AI read. Contacts scanned at the same event group themselves automatically.
STEP 2
The graph builds itself
AI reads your notes and extracts who they are, where they work, who they know, and what you promised. Every fact keeps a receipt — tap it to see the exact note it came from.
STEP 3
Ask, and act
Search your network in plain language. Get a follow-up draft that mentions the sailing thing. Get nudged when someone changes jobs — the moment outreach matters most.
What Dhaga remembers
More than a contact record.
Capture the context, connect it to the rest of your network, and use it when there is a reason to reach out.
02 · Auto-grouping
Circles form themselves.
Everyone you scan at the same event lands in one circle, automatically. Name it once — 'Web Summit 2026' — and it's an album of the day.
03 · Voice-first notes
Talk. Don't type.
A 30-second voice note becomes structured facts — role, intent, the sailing thing. Every fact keeps a receipt to the exact note it came from.
04 · The graph
It all connects.
People, companies, events, promises — one private graph that's yours alone. Drag the people. The threads follow.
05 · Ask
Search like you'd ask a friend.
“Who do I know in logistics?” Structured filters plus semantic search over every note you've ever taken — answers cited to your own words.
06 · Follow-up
Follow up the same evening.
One tap: a draft that mentions what you actually talked about. Sent while they still remember you too.
07 · Intelligence
Know before your competitors do.
Sarah announced she left Stripe — your watchlist caught it. Priya's back from Singapore — you noted it once; the graph remembered. The moments outreach matters, pushed to you.
08 · Warm paths
Every intro is two threads away.
Need a way into Aerolane? You've never met anyone there — but one note remembers Priya mentioning her old teammate Mei. The graph finds the path, and drafts the ask.
Answers with receipts
“Who did I meet in logistics with an AI budget?”
You’ve had that thought — and no way to answer it. Dhaga answers in plain language from what you actually observed: not a feed, not a guess scraped from the web, but your own notes, cited.
ask>
ask> who did I meet in Singapore who works in logistics?
Priya Nair — Head of Ops at Freightline. You met at TechInAsia, Oct 2025.
From your voice note: “…runs ops for a freight forwarder, they're evaluating route-optimisation AI next quarter…”
ask> who used to work at Stripe?
Sarah Chen — Now founding something new. You met at Web Summit 2026.
From your voice note: “…leaving Stripe in March, interested in our API, two kids, loves sailing.”
Try it
Play with a real-scale network
This is a fully synthetic, anonymized graph — thousands of people, companies and events you can pan, zoom and pull apart right in the page. Click any node to isolate its circle. Nothing loads until you ask.
~4,500 nodes · Anonymized demo network · loads only when you click
Compare
Everyone else stops at the contact.
d Dhaga that's us | BH Card apps Blinq · HiHello | MD Personal CRMs Mesh · Dex | A Enterprise Affinity | |
|---|---|---|---|---|
| Captures at the moment of meeting | ✓card, badge, QR, voice, chat | ✓cards & badges | —inbox sync only | —email mining |
| Voice-first notes → searchable facts | ✓with receipts | — | partial, typed | — |
| Ask in plain language | ✓ | — | partial | ✓ |
| Self-host it — your data, your server | ✓local-first core | — | — | — |
| Open source — read the code | ✓AGPL | — | — | — |
| Leave anytime with your data | ✓one file | CSV export | varies | contract terms |
| Price | $79/yr | $6+/mo | $10–18/mo | $2,000+/seat/yr |
Competitor pricing as publicly listed, July 2026. Affinity from $2,000/user/year (published).
Questions
Asked before you had to.
Early access
Build relationships. Keep the context.
Join the early-access list for Dhaga Cloud. The open-source core remains available to self-host.