AI Receptionist Pricing for Home Service Businesses (2026)

Every home service business asking "how much does an AI receptionist cost" runs into the same problem within five minutes of searching: the answer is a $25/month self-serve tool, a $200/month flat-rate plan, and a $3,000/month enterprise platform, all sitting in the same Google results page, all calling themselves the same thing.

That range isn't a data error. It reflects three genuinely different products wearing one label. Here's what actually separates them, what drives the number up or down, and the question that matters more than the price on the page.

Almost every AI receptionist on the market bills one of three ways.

Per-minute. You pay for time on the phone, typically $0.10 to $0.48 per minute. This is the model used by most of the enterprise-grade platforms built specifically for home services, including Avoca. It looks cheap on a pricing page and gets expensive fast once callers linger, leave voicemails, or ask a string of follow-up questions. A three-minute call and a nine-minute call are not the same bill.

Per-call. You pay a flat rate per answered call, usually $0.75 to $2.40, regardless of how long the conversation runs. This model is more predictable than per-minute and tends to reward tools that resolve calls efficiently rather than tools that keep callers on the line.

Flat-rate subscription. You pay a fixed monthly fee that includes a bucket of calls or unlimited coverage, typically $29 to $300 a month for self-serve tools, or a locked quote in the $1,000+ range for platforms with heavier onboarding and coaching layers attached. Overage past the included volume usually reverts to a per-call or per-minute rate.

The model matters more than the sticker price. A $49/month flat-rate plan and a $0.35/minute plan can land at nearly the same monthly bill at low call volume and diverge by hundreds of dollars once volume climbs.

Pulled together from public pricing pages and third-party pricing guides published in 2026, here's roughly where the category sits.

Self-serve, budget tier: $20–$99/month. Tools like AIRA and My AI Front Desk sit here, usually with a capped number of calls included and a per-call overage rate. Fine for a single-truck operation testing the category. Thin on integrations.

Full-featured flat-rate: $99–$300/month. This is where most small home service businesses land — providers like NextPhone ($199/month flat, unlimited calls) and similar flat-rate platforms bundle emergency routing, CRM sync, and calendar integration into one predictable bill. No per-minute meter, no surprise invoice.

Enterprise AI front-office platforms: $1,000–$3,500+/month. Avoca and Alivo sit here. Neither publishes pricing outright. Independent estimates put Avoca in the $1,000–$3,500/month range, billed per minute, and Alivo publishes a $1,299/month base tier (roughly $999/month on annual billing) plus add-ons for additional agent capacity. Both are built for operations with meaningful call volume — Avoca's public positioning skews toward $3M+ revenue shops running 5+ CSRs, and Alivo's pricing only pencils out past roughly 25–50 leads a month. We've written a full breakdown of what Avoca AI actually costs if that's the specific comparison you're running.

Traditional human answering services: $292–$1,100+/month. Per-minute human services like Smith.ai or Ruby still exist and still get compared against AI options. At 100 calls a month, they typically run 5–10x the cost of a flat-rate AI plan for the same coverage.

The honest range for a mid-sized home service business — one that wants real integrations and 24/7 coverage without an enterprise sales process — is $99 to $300 a month for the AI layer itself. Above that, you're usually paying for CSR coaching, outbound campaigns, or multi-location complexity that a smaller shop doesn't need yet.

The number on the pricing page is rarely the number on the invoice. Ask about these before signing anything:

Overage rates. What happens to your bill at double your normal call volume? Per-minute plans in particular can spike hard during a storm surge or a marketing push.

Setup and onboarding fees. Enterprise platforms often bundle weeks of onboarding into the quote. Ask what that includes and what happens if it runs long.

Integration scope. A "CRM integration" can mean a deep two-way sync or a basic webhook. The difference affects both price and how much manual cleanup your team does later.

Contract length. Some platforms lock in annual terms to get the advertised rate. Know what you're committing to before the discount looks good.

Per-seat or per-CSR charges. Coaching and analytics tools, common in the enterprise tier, often price by how many reps use them, not by call volume.

Pricing pages compare monthly cost. The number that should drive the decision is cost per missed call recovered, not cost per month.

If you're running paid search and paying somewhere north of $150 for a non-branded lead in a competitive trade, a missed call isn't a $0 outcome — it's a paid-for lead that called the next result on the page instead. Industry estimates for the average annual cost of missed calls at a typical small service business run into six figures once you account for lifetime customer value, not just the one lost job.

Compare that to a fully loaded human front-desk hire, which runs well into the $40,000–$60,000+/year range once payroll taxes, benefits, and turnover are factored in, versus $600–$3,600/year for most flat-rate AI plans. The math tends to favor AI receptionists heavily on pure cost — the real diligence is on what happens on the calls it actually handles.

Here's the part most pricing comparisons skip: two AI receptionists at the same price point can produce very different outcomes, because "answering the call" and "booking it correctly" are not the same feature.

Most AI voice agents in the trades — including several of the platforms above — store their business rules inside the model's prompt. That works fine until it doesn't: the model gets updated, a rule gets reinterpreted slightly differently, and bookings start drifting from what the business actually needs. A caller outside the real service area gets booked anyway. A job gets scheduled without accounting for the tech's actual drive time between stops. None of that shows up on the pricing page, and none of it shows up until the truck is already on the wrong side of town.

That's the distinction worth asking about on any sales call, regardless of which platform you're evaluating: are the scheduling rules enforced by a system, or interpreted by the AI in the moment? We've written more on why that distinction matters for scheduling specifically.

Driive approaches this differently. Dot, Driive's AI booking assistant, handles the conversation — but it can only confirm an appointment that a separate rules engine validates first: inside the service area, assigned to a technician who can actually make the drive time work, at a slot that fits the day's real schedule. The AI handles the talking. It doesn't handle the judgment calls that turn into a bad booking six weeks from now. Driive publishes tiered pricing built around your business size rather than a locked enterprise quote — you can see where your team lands in about 30 minutes. See it in action or explore the full platform breakdown.

Before comparing two providers' pricing pages side by side, get the same five numbers from each:

1. Your actual monthly call volume, including missed calls you're not currently tracking
2. Average call duration (this decides whether per-minute or flat-rate wins for you)
3. What's included at the base price versus billed as overage
4. Whether appointment booking is validated against real scheduling constraints, or just captured as a lead
5. Contract length and what it costs to leave if it doesn't work out

Whichever number wins on the page, run it against those five inputs before you sign.