dolv

Your AI operator for content, CRM, and GTM execution

4.8•8 reviews•

86 followers

Your AI operator for content, CRM, and GTM execution

4.8•8 reviews•

86 followers

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CRM software

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Marketing automation platforms

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AI Workflow Automation

Growth teams lose hours moving work between CRM, analytics, email, ads, and content tools. dolv brings that into one workspace. Give it a task: it reads your live funnel, does the work across your connected tools, and reports what shipped. Emails, posts, and ad changes wait for your approval before they go out. You keep the decisions. dolv handles the execution.

dolv Reviews

The community submitted 8 reviews to tell us what they like about dolv, what dolv can do better, and more.

4.8

Based on 8 reviews

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Other Reviews (7)

•3 reviews

What's great

I stumbled across Dolv while doom-scrolling Product Hunt one afternoon, looking for something to fix the chaos of jumping between HubSpot, Google Analytics, and our email platform every single day. Gave it a shot after reading a few comments and honestly, the "funnel-aware execution" angle hooked me immediately because most AI tools just spit out generic outputs with zero context about where your leads actually are.

After a few weeks in, the thing I genuinely appreciate is the approval queue. It sounds annoying on paper, but it's actually the right call. Any customer-facing action, whether it's an email draft or an ad change, sits in a queue for me to green-light before it goes live. That one feature alone stopped me from having the usual anxiety of "did the AI just send something embarrassing to 3,000 contacts?" The ~50 playbooks across different GTM disciplines are also a solid starting point, though some felt a bit too generic for our specific funnel setup.

What needs improvement

The playbooks need more customization depth. Right now they feel like solid templates, but when your funnel has niche stages or non-standard lead scoring logic, you end up having to work around the defaults more than you'd want. A more flexible "build your own playbook from scratch" mode, with proper conditional logic, would take this from a 4 to a genuine 5 for our team's use case.

vs Alternatives

Before landing on Dolv, I was testing Make.com and a custom GPT setup glued together with Zapier. They worked, sort of, but the amount of manual maintenance every time a tool updated its API was genuinely exhausting. Dolv being built specifically around GTM workflows, with native integrations already baked in, meant I wasn't spending weekends re-wiring automations just to keep the basics running.

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18 views1mo ago

•2 reviews

What's great

I stumbled across dolv through a PH thread about agentic GTM tools, and honestly I wasn't expecting much because there are so many "AI command centers" that just wrap a chatbot around your dashboard. Two weeks in and I'll say this: the Grounded AI piece is what separates it. It actually reads your company context, playbooks, live funnel data before doing anything, so the output isn't that generic AI slop you'd get from asking ChatGPT to "write a LinkedIn post for my brand."

The approvals queue is the other thing I genuinely appreciate. Anything that touches a customer (outreach, email sends, ad changes) gets staged for your review before it ships. Internal stuff like CRM scoring or tagging just runs. That split feels like a real product decision, not an afterthought.

What needs improvement

Batch approvals for lower-risk external actions would be a solid QoL improvement. And I'd love to see more integrations, especially for CRM tools outside the Google/Microsoft orbit. The funnel intelligence view is great but could use a bit more flexibility in how you define funnel stages for non-standard GTM motions.

vs Alternatives

Looked at building something similar with a Zapier + Make combo layered with Claude or GPT API calls. It works, technically, but the second a task needs to read live funnel context and decide between three actions instead of just firing a preset trigger, the whole thing falls apart. dolv handles that decision layer natively, which is the actual hard part.

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8 views1mo ago

•2 reviews

What's great

Came across dolv while looking for something that could actually execute GTM work, not just suggest it. I'd been running growth for a small team with 6-7 tools open at once and was manually moving context between all of them every single week. Tried dolv for about two weeks, mostly for content scheduling, CRM updates, and funnel reporting, and the thing that genuinely surprised me was how it reads your live funnel first before doing anything, so the output actually makes sense for your specific situation rather than being generic AI filler.

The approval queue for customer-facing actions is the feature I didn't know I needed. Email drafts and post schedules sit in a review step before anything goes out, which sounds annoying in theory but in practice gives you just enough confidence to let the internal stuff like lead scoring and deal stage updates run on its own. It's a pretty small UX decision that changes how much you actually trust the tool day to day.

What needs improvement

The approvals queue can become a bottleneck if you're running a lot of customer-facing tasks in parallel, every action needs a manual click and that adds up. Some kind of batch approve or conditional auto-approve for lower-risk sends would help a lot. More integrations beyond the current set would also open it up for teams running less common stacks.

vs Alternatives

Looked at building a Zapier or Make stack with some AI steps layered on top. It works fine for trigger-based tasks but falls apart the moment a workflow needs to read context and make a decision rather than just fire on a condition. That gap is basically what dolv is built to fill, and it shows.

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29 views1mo ago

•7 reviews

What's great

The approvals gate is great, it splits actions by reversibility, so customer-facing sends wait for you while internal work like lead scoring or CRM updates just runs. Also, grounding everything in your live funnel instead of a blank chat box is what keeps the output from being generic filler

What needs improvement

The approvals queue perhaps. If every customer-facing action needs a manual click, it might risk a bit of a bottleneck it's meant to kill

vs Alternatives

weighed whether a Zapier or Make stack with a couple of AI steps bolted on would cover this, but that falls apart the moment a task needs to read context and decide rather than fire on a trigger

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28 views1mo ago