I've tried them all - Salesforce, HubSpot, Pipedrive, Attio. Every single one of them felt like I was feeding data into a system just to generate dashboards nobody reads. Clarify is the first CRM that actually gives back.
The AI layer is genuinely impressive. After a few weeks, it started connecting dots I hadn't even noticed - surfacing stale deals, prepping context before calls, and summarizing threads without me lifting a finger. As a founder running sales myself, this is exactly the kind of leverage I needed. The clean, distraction-free interface is a huge plus too. No bloat, no unnecessary clicks. It just gets out of the way.
Clarify
Hey Product Hunt!
When we started Clarify, we promised you an autonomous CRM. Today, we make good on that promise with our take on Agents. We’re pumped to launch it today!
They trigger on a schedule or a signal, run across your stack, and work directly with your CRM data.
You describe what you want in plain English. Clarify builds it. You control what each agent can read, write, and do.
We also built a template library so you don't have to start from scratch — pipeline digests, lead enrichment, data hygiene, call coaching. Pick one, customize it, ship it.
This is the feature I've wanted to put in front of users since we started the company.
Curious to see what you build with it!
— Patrick
The autonomous part is exciting, but the failure mode I'd worry about in a CRM specifically is a confidently-wrong write — merging the wrong duplicate, enriching a lead from a stale source, updating a field based on a misread signal. A bad autonomous write is worse than no write because it silently pollutes the source of truth and everyone downstream trusts it. Question for you Patrick: does Clarify ever say "I'm not sure" and hold instead of acting, or does every triggered agent always write something?
Clarify
@david_marko Totally fair concern. we worry about the same failure mode.
Clarify agents don’t have to write on every run. You can configure write-capable tools to require approval (or even deny them) per tool, per agent so if the agent isn’t confident, the safe pattern is that it pauses and asks before taking the risky action, instead of “silently shipping” a change.
The 'relationship agents' framing is interesting — the hard part with any AI layer on a CRM is trusting the underlying data, since reps under-log and records go stale fast. Does the agent actively enrich/verify (pulling from email, calendar, web) to fill the gaps, or does it reason over whatever's already in the CRM? The first is far more useful but also where accuracy gets tricky.
Clarify
@mikebrandswarm Yes! We connect to email, calendar, and web to fill the gaps. You can build agents to manage both the manual data entry (closed won reasons, etc.) as well as create records like our deal creation agent that looks at call transcript, email, + usage data.
ChatWebby AI
The "set them fully autonomous or require approval before acting" toggle is the part that stands out to me — that's usually where automation tools force an all-or-nothing choice. Is the approval gate configurable per action type (e.g. let enrichment run free but always hold writes that overwrite existing CRM fields), or is it set at the agent level?
Clarify
@zain_sheikh you can do it per action/tool on the agent.
The interesting bit is not that the CRM can update fields. It is the authority model around each update: which signal triggered it, what data it touched, whether approval was required, and what receipt proves it happened.
How are you exposing that when an agent runs fully autonomously?
Clarify
@blah_mad We have an activity log of every change on a record, including the actor. Actions from agents are associated with an agent run, which includes the entire reasoning context.
DMV by Agent Community
I like the idea that the CRM work finally moves into the background.
A lot of the painful part is not managing relationships, but keeping the system clean enough so those relationships don’t get lost. Pipeline digests, lead enrichment, and data hygiene feel like exactly the right things for agents to handle.
Personally, I’d probably start with follow-ups and pipeline summaries first. Curious what teams automate most often after setup: cleanup, enrichment, follow-ups, or reporting?
Clarify
@andrasczeizel the "follow-up agent" is probably the most helpul and often the first thing to go when folks get busy. It was the first agent that I built, followed by my "inbox reply drafter" that drafts replies for me automatically with our business context.
The idea of a CRM that updates itself is appealing because manual data entry is everyone's least favorite part of sales. I'm curious, what's the biggest habit founders stop doing once they switch to Clarify?
Clarify
@harini_mukesh having to think about updating their CRM. We've focused so much of our time on making it simple to use and the agents do the heavy lifting. So when you need to ask questions via Rep/Claude, etc. you have a reliable source of all of your customer data.