Assay

Genuinely useful — missed calls are such a silent revenue leak for small teams. Does Assay handle spam filtering differently for inbound vs outbound?

I was acquainted with someone who needed a voice AI system for the DACH recruiting market; outbound screening calls to applicants, structured scoring, automatic routing. I built it, and it worked well enough that I spent the next year on almost nothing else, electing to spend my time chasing tighter scoring across conversation types, the edge cases that break simpler approaches, the regulatory differences between markets. Somewhere in there I stopped building financial models entirely and started dialing this in full-time. Assay is what came out the other side; the same core idea, with everything unreliable removed. Feel free to hit up our demo line, and be as adversarial as you like. We are eminently confident in the product.

Valid business application for voice AI agent.

When a call gets a low score, does Assay keep trying to reach the lead later or does it stop based on the first call's result?

The lead scoring on every call is the part I would like to understand better. When the score is produced automatically from 0 to 100, what is it actually based on for an outbound call that lasted forty seconds and ended with "call me next month"? In my experience that call is often the best lead on the list, but it looks like a failure in any metric built on call length or sentiment. Related question: you mention non-responders are held in a reactivation sequence rather than written off. Who decides the cadence of that sequence, and can the owner of the list see and change it, or is it part of the done-for-you setup? I ask because at $699 a month a one-person business needs to know whether it is buying a system it can steer or one it has to trust blindly.

amazing, really love it

Scoring every call 0 to 100 is the interesting part. Will there be a one-line reason next to each score, like 'no budget mentioned' or 'outside service area'? That would make the score easier to trust and make it quicker to spot the calls it got wrong.

Really solid concept! Clean call filtering and triage solves a huge headache with spam and interruption workflows. Does Assay support custom rule sets or CRM integrations for flagged calls? Congrats on the launch!

Folding a TCPA consent check, DNC scrub and calling window check into every outbound dial is a thoughtful touch for home services and law firms working old lead lists. If the voice model minutes behind all those scored calls ever start to pile up, PZERO offers more affordable AI capacity at pzero.studio.

The FCC's 2024 ruling treats AI-generated voices as "artificial voice" under the TCPA, so AI outbound marketing calls need prior express written consent, not just "not on the DNC list". Does your consent gate check specifically for written consent? And does the agent say it's an AI at the start of a call? A few states now expect that too.

The part about scoring calls and only putting the valuable ones on your calendar is interesting. A lot of tools focus on handling more calls, but deciding which ones actually deserve your attention seems just as important. Curious how well it works for businesses with very different types of customers.

Interesting to see recruiting listed as a use case. How do you show why a call got its score? In hiring, a number alone is hard to trust, so being able to point to the reasons behind it makes a big difference.

I like the idea of scoring every call automatically instead of making teams dig through dashboards. Filtering for conversations that actually deserve your time feels like a much more useful approach to sales automation.

Deciding what matters is the hard part of any triage tool. How does Assay learn what's important to a particular person? And when it lets something through that shouldn't have, or holds back something that should have rung, how does the user correct it?