Outcraft AI's new per-lead pricing for its inbound AI SDR agents is a useful, concrete example of what buying a productized lead-qualification tool actually costs and what it does not include: the criteria for what counts as a qualified lead. On September 10, 2026, Outcraft AI replaced its earlier flat monthly license and per-minute billing with a straight per-lead charge, counted only once its AI SDR has engaged that lead, at rates from about $3 per lead at low volume down to under $1 per lead at scale (GlobeNewswire, September 2026). That is a real, dated pricing page, not a hypothetical, and it draws a clean line between what a productized SDR agent sells and what a business actually needs when the question is not "was this lead engaged" but "was this lead qualified on our terms."
Key Takeaways
It charges for engagement, specifically, the AI SDR reaching out to and interacting with a lead, at rates that step down with volume: about $3 per lead at a 100-lead entry tier, $2 per lead at 1,000 leads a month, and under $1 per lead above roughly 4,000 leads a month, with voice, SMS, email, and WhatsApp channels included at every tier and no setup fees or per-user charges (GlobeNewswire, September 2026). The billing event is engagement, a lead the agent talked to, not qualification, a lead that fits what the business is actually trying to sell.
That distinction is the whole story. A tool billed on engagement has every incentive to engage more leads, because that is what generates the charge. Whether the lead was worth engaging in the first place is a separate question the pricing model has no stake in answering.
Because engagement is a generic action a tool can perform on any lead, while qualification requires knowing what this specific business considers a good fit, and that knowledge does not ship in a box. A productized AI SDR can be configured with scripts and rules, but the judgment calls that actually separate a real prospect from noise, the follow-up question that reveals budget, the objection that reveals the lead is shopping three competitors and will not close, the answer that reveals they are not decision-makers, get thinner the more the tool is built to work identically across every customer buying it.
This is not a flaw unique to Outcraft AI. It is the tradeoff every productized agent makes to be sellable at scale: the more generic the qualification logic, the more businesses can buy it unchanged, and the less precisely it reflects any one business's actual definition of a good lead.
It is built around your specific criteria instead of a generic engagement model. When lead qualification is one of the roles we build as part of an AI team, the qualifying questions, the disqualification reasons, and the handoff rules come from what you already know about which leads close, written into the spec before anything ships, under two human gates, you approve the plan, you review the work. The AI Qualifier answers every inbound lead and qualifies it on your criteria, then books or disqualifies it with a stated reason, which is a different job than engaging a lead and counting it.
Cost shape differs too. We do not charge per lead engaged; the reasoning behind a flat function-based retainer instead of usage metering is covered in the pricing post linked above. The narrower point here: a productized tool's qualification logic is generic by design, and a business whose good-lead definition is specific gets a better result from a role built around that definition than from a tool that bills for engaging more of them.
This holds across verticals: what counts as a qualified lead for a law firm looks nothing like what counts as one for an HVAC company, which is exactly the kind of distinction a generic engagement-based tool cannot encode; see the industries pages for how the AI Qualifier role plays out by vertical.
Not directly. Outcraft AI sells a productized AI SDR tool that any business can adopt unchanged; we build and run an AI Qualifier role scoped to one business's specific criteria as part of a broader AI team. Outcraft AI is useful here as a real, dated example of how productized agent pricing works, not as a like-for-like comparison.
Not inherently. It can make sense for a business that wants a low-commitment way to test an SDR tool without staffing anyone to manage it. The tradeoff is that the pricing measures engagement, not fit, so a business still needs to define what "qualified" means and check the tool's output against that definition itself.
There is no published rate card on either side of that comparison for us; scope determines the number, and it arrives in a written proposal after a written intake. The more useful comparison is not price alone but what each option encodes: a generic engagement model you configure, or a qualification role built around your specific criteria from the start.
Yes, and that is a reasonable sequence for a business still discovering its own qualification criteria. The signal to make the switch is usually when the generic tool's engagement volume stops correlating with actual closed deals, which means the criteria it is missing have become the bottleneck.
Outcraft AI's per-lead pricing is a clean, current example of what a productized SDR agent actually sells: engagement, billed by volume. If what your business needs is leads qualified on your own terms, not just leads talked to, send a written intake describing your criteria, and the proposal that comes back is scoped to build around them.
Internal links to add from older posts within a week: anchor "usage-based AI pricing" pointing to why-we-dont-charge-per-token-or-seat; anchor "AI lead qualification" pointing to how-to-get-ai-lead-qualification; anchor "AI Qualifier role" pointing to how-to-get-ai-team-for-small-business.
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