Dhaga vs folk: Team Relationship Intelligence vs Your Own Memory
folk vs Dhaga compared honestly — folk's Strongest connection tells you which teammate knows a prospect; Dhaga tells you what you know about them. Pricing, export, and graph depth.
The short version
folk is a seat-priced CRM for GTM teams, and it is genuinely good at something people wrongly assume it lacks: it has relationship intelligence, shipped and paid for, called Strongest connection — it scores who on your team knows a prospect best. Dhaga has nothing like folk's outbound engine, pipelines, enrichment waterfall, or its 30,000-user Chrome extension, and it holds no SOC 2 attestation. The real split isn't "graph vs no graph," it's whose relationships get modelled: folk maps your teammates' access, Dhaga maps your own memory of a person and what you promised them. If you have a sales team, folk is probably the answer; if you work alone, folk's headline feature switches off entirely.
If you've been comparing folk vs Dhaga, you have probably read a few lazy takes claiming folk is "just a contact list with no network view." That's false, and it's worth clearing up in the first paragraph: folk sells relationship intelligence on every tier, its help centre pitches it exactly the way you'd expect — "Have you ever wondered if anyone on your team already knows a prospect you want to contact?" — and it works. So this comparison is about a subtler and more useful distinction: the shape of the relationships each tool stores.
Full disclosure up front: I build Dhaga, so treat every claim here as one you should verify. I've tried to be scrupulous about folk's strengths, partly because they're real and partly because overstating a competitor's gaps is how you lose the argument the moment a reader opens folk's pricing page.
The core difference
folk's edge always runs teammate → contact. Its Strongest connection score asks: of the people in this workspace, who has the best claim on this person? It's a good model and a carefully built one — the score weighs interaction volume, how long the relationship has run, whether the exchanges were one-to-one or group threads, whether they're bilateral, and how recent they are. If you run a twelve-person sales team, that answer is worth money, because it routes an intro request to the right colleague in one click.
Dhaga's edge runs contact → contact, and it comes out of what you already wrote. You dictate a note after a dinner — "she introduced me to her old CTO, he's raising" — and Dhaga extracts the people, links them to each other, and stamps each relationship with the id of the note that produced it. Nobody drew that line by hand. That's the product thesis: your notes already contain your network, and typing it in twice is the failure mode.
Two consequences fall straight out of that difference, and they're the ones that should decide your choice.
folk's relationship intelligence requires teammates. Their own documentation says it plainly: Strongest connection is only calculated if you have teammates in your workspace and those teammates have shared their interactions. A solo founder, an angel, a consultant, a solo recruiter — anyone with a workspace of one — pays $24 to $60 a seat for a feature that structurally cannot produce a result. folk's contact-to-contact field does exist, but it's manual, one-way by design (their docs: "the relationship is only 1-way between the contacts"), scoped to a group, capped, and left out of exports.
Dhaga models what you said you'd do, not just who you know. A note becomes facts, typed relationships, and follow-ups with dates attached. That's a different job from scoring access, and neither tool does the other one's job well.
Where folk wins
I'd rather be blunt about this than have you discover it after signing up, so here is the honest list — and it's long.
- A real outbound engine. Sequences, custom sending domains, reply tracking, campaign analytics. Dhaga has none of this and isn't building it. If your CRM has to send the emails, folk wins by default.
- Deals, pipelines, and dashboards. folk is a sales CRM with a personal-CRM feel. Dhaga has no pipeline concept at all.
- The folkX Chrome extension. Around 30,000 users, a 4.8 rating, one-click capture from eight-plus platforms. Dhaga's extension exists but has never been submitted to the Chrome Web Store — it's load-unpacked only, which is a meaningfully worse experience.
- Waterfall enrichment across six vendors. Dhaga does not chain enrichment providers. Worth noting that folk's own docs are refreshingly candid that enrichment "only work[s] around 50-60% of the time" — but 50-60% of something beats none of it.
- A versioned REST API and a hosted MCP server with 34 tools. Dhaga ships an MCP server too, with a much smaller surface.
- SOC 2 Type I. Dhaga has no SOC 2 attestation today. If your procurement team asks, that's a hard stop.
- Shipping velocity and a real company behind it. Roughly $10M ARR, about $9M in seed funding, around 25 people — and card scan, voice notes, MCP, and mobile all landed within the last 60 days.
- Strongest connection itself. For a team, it's the best implementation of "who here knows this person" I've used.
folk's real weak spot isn't a missing feature; it's depth. A Product Hunt reviewer put it well: "There's only one 'dimension' in the entire app, which is 'People'." And a Capterra reviewer from investment management, rating it four stars, said something sharper: "it's so clean that it feels like I'm not making the best use of that deep network/relationship data." That's the gap Dhaga is aimed at.
Where Dhaga wins
Ambiguity becomes a question, not a wrong edge. This is the mechanism I'd want you to judge us on. When a note mentions a first name you have three of, Dhaga does not pick the most likely one and quietly write a relationship. It raises a pending confirmation and waits for you. A CRM that guesses is worse than one that asks, because a wrong edge is invisible — you find it months later, in front of the person, when you act on it. Every edge in your graph is therefore something you wrote or something you confirmed.
Provenance you can see, and deletion that actually deletes. Every AI-derived fact carries a visible receipt button — "Highlight the note this fact came from" — that jumps you to the sentence responsible. Relationships are tied to their source note and are deleted with it. Deleting a note is transactional: it tombstones that note's facts, edges, positions, tag receipts, card photos and its embeddings. That last one matters more than it sounds. Plenty of AI CRMs orphan the vector index, so content you deleted stays semantically searchable forever.
Warm-intro path-finding that works for one person. Dhaga walks your own graph to find the shortest path from you to someone you want to reach. It's pure traversal — no model call, no AI credits, nothing sent to a provider — and unlike Strongest connection, it needs no colleagues to function.
An export you can actually leave with. folk's export runs group by group, covers contacts and notes only, and explicitly excludes interactions, custom fields, and Strongest connection scores; their docs state "We currently don't allow exporting from the whole workspace." folk also stores full email bodies with, in their words, no setting to store metadata only, and auto-deletes workspaces after 90 days of inactivity. Dhaga's export is the whole graph, self-serve, any time.
No contact quota, and a free tier that exists. There is no contact cap anywhere in Dhaga's code. folk has no free tier at all — a 14-day trial, then a seat price.
Self-hosting on request, and Indian pricing. For enterprise teams with a data-residency requirement, Dhaga will provision a deployment on infrastructure you control. folk is US-only (AWS us-east-1), with no EU region, no self-hosting, and Google-only SSO on every tier.
One caveat stated plainly, because the section above is a sales pitch otherwise: Dhaga's AI features — extraction, natural-language recall, drafting — are the paid tier. The free tier gives you 10 AI credits a month and is a manual CRM after that.
Feature by feature
| Dhaga | folk | |
|---|---|---|
| Relationship intelligence / connection scoring | Contact-to-contact | Teammate-to-contact |
| Works with no teammates | Score needs a team | |
| Relationships extracted automatically from notes | Manual, 1-way | |
| Visible source note on every fact | — | |
| Full-workspace export | Group by group | |
| Free tier | 10 AI credits/mo | 14-day trial |
| Outbound sequences, pipelines, dashboards | — | |
| Chrome Web Store extension | Roadmap | |
| SOC 2 | — | Type I |
Read the bottom three rows as carefully as the top three — they're the reason a good number of readers should close this tab and go sign up for folk.
Pricing, read honestly
folk is $24 per seat per month billed annually, $30 monthly; Premium is $48 annual and $60 monthly; Enterprise starts at $80 and $100. There is no free tier — you get a 14-day trial and then you pay. Dhaga is free to start with 10 AI credits a month, and Pro is $4.99/month billed monthly or $48/year. In rupees, Dhaga Pro is ₹499/month or ₹4,799/year — against roughly ₹25,000 per seat per year for folk's entry tier at annual pricing, before you add a second seat.
The comparison isn't quite like-for-like, and I'd rather say so than win on a technicality: folk's price buys an outbound engine and a team workspace. If you'll use those, the seat cost is easily defensible. If you're one person who came for the relationship graph, you're paying a team price for a feature that won't compute. This comparison is current as of August 2026 — verify current pricing and plans before you commit. For the wider field, our best personal CRM apps in India roundup puts both in context.
Which should you choose?
| If you… | Choose |
|---|---|
| Run a 5–50 person GTM team and need "who here knows them?" | folk |
| Need sequences, pipelines, dashboards, or a versioned API | folk |
| Need SOC 2 or a mature browser extension today | folk |
| Work alone and want a relationship graph that still functions | Dhaga |
| Want relationships extracted from notes, with a visible source | Dhaga |
| Want deletion that clears the vector index too | Dhaga |
| Need Indian pricing, or self-hosting for a data-residency rule | Dhaga |
The honest test: if your bottleneck is "which colleague can introduce me," buy folk. If your bottleneck is "what did I promise this person in March," that's a different tool.
The takeaway
folk built a genuinely good answer to a team problem, and it is further along than Dhaga on nearly every axis that involves selling to someone. If you have colleagues whose interactions can be pooled, Strongest connection is the feature you came for, and no amount of graph purism from me should talk you out of it — go use folk.
But if your workspace is you, folk's best feature never fires, and what's left is a very clean contact list at a seat price. That's the reader Dhaga is built for: relationships pulled out of your own notes automatically, ambiguity raised as a question instead of a silent wrong guess, every fact showing the note it came from, and an export that takes the whole thing with you. If warm intros are the specific job, warm introductions and mutual connections goes deeper on the mechanics, and Dhaga vs Dex covers the automatic-capture trade-off that folk and Dex both make.
Discussion
Dhaga vs Dex: Private CRM vs Auto-Sync CRM
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Dhaga vs Mesh: Network Mapping at Scale vs Memory With Receipts
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