Dhaga vs Mesh: Network Mapping at Scale vs Memory With Receipts
Mesh (formerly Clay) vs Dhaga compared honestly — Mesh maps the people in your network across the globe; Dhaga records what you know about them and what you promised. Pricing, capture, and provenance.
The short version
Mesh — the app formerly called Clay, acquired by Automattic in June 2025 — manages more than 150 million relationships and has the best automatic capture in the category, plus a genuinely impressive interactive map of your network and the first immersive 3D network visualisation on Apple Vision Pro. Dhaga has none of that reach: no automatic email or social capture, no native apps in the stores, no SOC 2. What Dhaga has is the other half of the problem — Mesh models who someone is, and it doesn't model what you said you'd do about it. If your gap is "I don't know who's in my network," get Mesh. If your gap is "I know who they are and I've forgotten what I promised," keep reading.
If you're weighing Mesh vs Dhaga, start with a disambiguation that trips up almost everyone: Mesh lives at me.sh and is not clay.com, the B2B sales-data company. Different founders, different category, confusingly similar former name. The Mesh in this comparison is the personal network app that rebranded from Clay on 20 March 2026 and now describes its mission as helping you "map, understand, and activate networks at scale."
Full disclosure up front: I build Dhaga. That makes me the least neutral person to write this, so I've tried to concede Mesh's advantages in more detail than a fair reviewer would bother with — starting with the one people most often get wrong about them.
The core difference
Let me put the most important honesty point first, because a competitor claiming Mesh has no network view would be flatly wrong. Mesh has network visualisation, and it's better looking than ours. Their interactive Map View runs on Mac, Windows, web, iOS and Android and, in their words, lets you "visualize your entire network across the globe" while staying "smooth even with tens of thousands of connections." They also shipped the world's first immersive 3D network visualisation on Apple Vision Pro. They renamed the entire company around this idea. Anyone telling you Mesh is a flat contact list has not opened it.
Here's the distinction that actually separates the two products. Mesh's map is primarily geographic — it answers where your people are, which is a genuinely useful question when you're planning a trip to Singapore and want to know who to see. A person-to-person relationship topology — the shape of who knows whom — exists in their immersive Vision Pro experience, not as the everyday view on the platforms most people use.
And there's a second, sharper difference that an independent audit of the two products put well: Mesh "tracks contact info but not conversation history or promises made." That is the split in one line. Mesh is superb at assembling an accurate, current record of who a person is — title, company, location, last touch, job changes. Dhaga's job starts after that: taking the messy note you dictated in a taxi and turning it into structured facts, typed relationships between the people you mentioned, and follow-ups with dates, each one traceable back to the sentence that produced it.
Neither is a substitute for the other. They fail in opposite directions: Mesh will tell you about a person you barely remember meeting; Dhaga will remember the thing you promised and know nothing about anyone you never wrote down.
- 150M+
- Relationships managed
- 2025
- Acquired by Automattic
- 7
- Platforms + 5 browsers
- ~80%
- Of a contact record auto-filled
Where Mesh wins
The list is long and I'd rather you get it from me than from a review site after you've signed up for the wrong thing.
- Automatic capture, at a level nobody else matches. Gmail, Outlook, calendar, LinkedIn, X, iMessage, WhatsApp and Facebook feed it, and roughly 80% of a contact record fills itself. Dhaga has no ambient background feed — you capture deliberately.
- Reach. Seven platforms and five browser extensions, with Android landing on 12 August 2026. Dhaga's mobile app is a development build that has never been submitted to either store, and its browser extension has never been submitted to the Chrome Web Store. That's a real gap, not a roadmap footnote.
- Job-change detection and relationship-strength scoring. Both mature, both absent from Dhaga.
- Map View, on every platform, plus the Vision Pro visualisation. Conceded above and worth repeating.
- A read/write MCP server, SOC 2 Type II, and HIPAA on the Teams plan. Dhaga ships an MCP server but has no SOC 2 attestation and no HIPAA posture at all.
- Automattic's balance sheet. The company behind WordPress.com, Tumblr, and Beeper acquired them. Whatever risk you price into a small independent tool, Mesh carries less of it.
- A privacy stance that deserves credit rather than an attack. Mesh says "Mesh does not own your data, nor do we sell it… It's your data, period," runs AI as opt-in, and doesn't train on user data. I'm not going to insinuate otherwise — our contrast is self-hosting and provenance, not carelessness.
Mesh's weak spots come from its own App Store reviews and they cluster in one place: hygiene. One reviewer wrote that "Clay is super buggy and unfocused on its core promise" with "zero features around automated duplicate resolution"; another put it more plainly — "duplicates will drive you insane." There are no custom fields. A reviewer complained they "couldn't filter by network strength or find contacts meeting specific criteria." And Nexus, their AI layer, is still in early access three years after launch, described by one user as "more of a toy." Auto-capture at this scale produces a lot of records; deduplicating and querying them is where users report the friction.
Where Dhaga wins
Ambiguity becomes a question, not a wrong edge. Lead with this one, because it's the direct answer to the duplicate complaints above. When a note mentions a name that matches two people you know, Dhaga does not guess. It raises a pending confirmation and holds the relationship until you resolve it. A silently wrong edge is the worst failure mode a relationship tool has, because you don't discover it in the app — you discover it in front of the person.
Relationships are AI-derived from your notes, and every fact shows its source. Dhaga reads a note, extracts the people in it, and writes typed contact-to-contact edges automatically. Each fact carries a visible receipt button — "Highlight the note this fact came from" — so you can check any claim against the sentence that produced it. Relationships are tied to their source note and deleted with it.
Cascade delete is transactional and includes the vector index. Deleting a note tombstones its facts, edges, positions, tag receipts, card photos and its embeddings, in one transaction. Most AI CRMs orphan the vector index, so deleted content stays semantically searchable indefinitely. If you take a "forget this person" request seriously, this is the part to check in any tool you're evaluating.
Warm-intro path-finding at zero AI cost. Traversing your own graph for the shortest path to someone is pure computation — no model call, no credits, nothing leaving your instance — and it works for a single user with no team.
Promises, not just people. Notes become follow-ups with dates, surfaced on one plan view. This is the "conversation history and promises made" half that Mesh doesn't model.
Self-hosting on request, and pricing in rupees. For enterprise teams with a data-residency requirement, Dhaga will provision a deployment on infrastructure you control — never a public download, always an arrangement. That matters more in India than the feature lists suggest, and there's a related point: a neutral reviewer noted Mesh's enrichment weakens for "offline professionals" and in "non-US markets where LinkedIn adoption is lower." Auto-capture is only as good as the platforms your network actually uses.
Stated plainly so this section isn't a pitch: Dhaga's AI — extraction, natural-language recall, drafting — is the paid tier. Free gives you 10 AI credits a month; after that it's a manual CRM.
Feature by feature
| Dhaga | Mesh | |
|---|---|---|
| Network visualisation | Relationship graph | Geographic map + 3D on Vision Pro |
| Relationships extracted from notes automatically | — | |
| Visible source note on every fact | — | |
| Follow-ups and promises tracked | — | |
| Delete cascades to the vector index | Not documented | |
| Contact cap on the free tier | None | 1,000 contacts |
| Automatic capture from email, calendar, social | — | |
| Native apps in the app stores | Roadmap | |
| SOC 2 / HIPAA | — | Type II + HIPAA |
The bottom three rows are not consolation prizes for Mesh. For a lot of readers they're decisive, and I'd rather you weigh them at full strength.
Pricing, read honestly
Mesh has a free tier up to 1,000 contacts, but it asks for a credit card at signup — worth knowing before you call it free. Pro is $19.99/month, or $119.99/year, which works out to roughly $10/month for unlimited contacts. Teams runs $40–49 per seat per month.
Dhaga is free to start with 10 AI credits a month and no contact cap anywhere, and Pro is $4.99/month monthly or $48/year. In rupees that's ₹499/month or ₹4,799/year. So at the individual tier Dhaga is about a quarter of Mesh's monthly sticker and under half its annual one, which makes budget a real difference rather than a tie-breaker. Mesh's annual Pro is the better deal against its own monthly price; Dhaga's free tier is the more usable one if you never intend to pay, since it isn't gated behind a card. 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 covers both alongside the rest.
Which should you choose?
| If you… | Choose |
|---|---|
| Want your network assembled for you from email and social | Mesh |
| Want to see where your contacts are in the world | Mesh |
| Need apps on every platform, SOC 2 Type II, or HIPAA | Mesh |
| Need to remember what you promised, not just who they are | Dhaga |
| Want every fact to show the note it came from | Dhaga |
| Want deletion that clears embeddings, not just rows | Dhaga |
| Live in a market where LinkedIn coverage is thin | Dhaga |
A blunt way to choose: Mesh is a map. Dhaga is a memory. Buying a map when you needed a memory is the expensive mistake here, and so is the reverse.
The takeaway
Mesh is the more finished product by a wide margin, and its automatic capture is the best in the category — if your honest problem is that your network exists in eight inboxes and you've never seen it in one place, Mesh solves that today and Dhaga does not. Go use Mesh. The Automattic acquisition makes it a safer bet too, and I'd rather say that clearly than pretend a two-year-old tool has closed a gap it hasn't.
What Mesh doesn't do is remember the specific thing you told someone you'd send them. That's the job Dhaga took: notes become facts and relationships automatically, ambiguity gets raised as a question instead of resolved by a guess, every fact shows the note behind it, deletion cascades all the way through the embeddings, and warm-intro paths come from graph traversal that costs nothing. If you want the ownership argument in more depth, Dhaga vs Monica covers the self-hosted lane, and Dhaga vs Dex is the closest comparison to Mesh's automatic-capture bet.
Discussion
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