Running a contact center with humans is one of the most expensive line items in any consumer-facing business. ~2.85M customer service representatives in the US sit at ~$40k/year fully loaded — a $100B+ annual US wage bill that's structurally exposed the second voice agents cross the quality bar.^[11] Globally the number is closer to 17M workers.

The existing voice AI category handles the easy 30% — order status, store hours, password resets, simple routing. That's the IVR-replacement use case, and it's already crowded. The complex 70% — exceptions, escalations, claims, billing disputes, retention saves, multi-step workflows that touch the CRM and the billing system — is where the headcount actually lives, and it's where the incumbents have been the slowest to ship.

Leaping picked the hard end of the distribution as its wedge. Hawesko (Germany's largest wine merchant) runs >1,000 calls per day with 70% autonomously handled in wine purchasing.^[2] A US-bound Jamaican BPO running ACA pre-qualification processes >5,000 calls per day with one minute saved per call.^[2] Thompson Creek Window Homes — a $100M+ home services business — runs Leaping for AI-driven appointment scheduling.^[1] These aren't FAQ bots. They're full call flows that move money and time.

LLM inference costs dropped 60–85% across 2023–24. For the first time, sub-second voice latency at gross margins that work for a SaaS business is structurally possible. The 2022 voice AI category was racing a cost curve; the 2025 category is on the cost curve's good side.

TTS crossed the uncanny line. Customers no longer hang up when they hear an AI voice. 61% of new buyers prefer faster AI responses to waiting for a human.^[6] The buyer-side resistance that capped category penetration for a decade is gone.

Customer expectations forced enterprise adoption. 80% of contact centers already use some form of AI; 76% plan to boost AI investments in the next two years.^[6] AWS, Salesforce, and the platform giants are now treating customer experience reinvention as the keynote of every earnings call.^[7] The category has moved from experiment to multi-year contract motion.

And the capital market has since repriced the whole category. Sierra went $4.5B → $10B → $15B+ in nineteen months, closing a $950M Series E in May 2026.^{[9] [15] [17]} ElevenLabs tripled to $11B in a single year on the strength of its agents push.^[18] 2026 is also the year Gartner's landmark forecast comes due — $80B in contact-center agent labor costs removed by conversational AI.^[24]The deflation thesis stopped being a slide and became a P&L line.

More calls → better prompts. Every customer interaction is structured training data. The autonomous A/B test loop chooses the better prompt variant on outcome metrics — containment, CSAT, transfer rate, resolution latency — without engineering involvement.^[3]

Better prompts → higher containment. Hawesko's deployment started at basic call handling and progressively improved to 70% autonomous purchase-call completion while maintaining 90% CSAT. That happened without the customer's team manually reviewing or updating prompts.^[5]

Higher containment → more contracted volume. Every percentage point of containment is a budget unlock for the customer. Leaping captures that unlock as expanded call volume — the textbook land-and-expand motion for voice AI. NRR scales with talk-time, not seats, which is the right shape for the category.

Claims status that requires a policy lookup. Not a Q&A — a multi-step flow that reads the policy system, applies the deductible rules, and reports back in natural language. The integration is the product; the LLM is plumbing.

Appointment scheduling against real inventory. Thompson Creek doesn't need a calendar bot — it needs an agent that respects technician availability, parts inventory, and zip-code routing rules. Leaping ships into the integration layer of that business, not the front-end of it.^[1]

Retention saves that update the subscription. The agent applies the offer, writes the change to billing, and confirms with the customer. That's an end-to-end workflow that incumbents historically required a Tier-2 human agent to complete.

Warm transfers that carry context. When the agent does need to escalate, it hands the human seat the full call history, the customer's intent, and the recommended next action — no "tell me your story from the beginning."^[12]

US customer service representatives: ~2.85M, fully loaded at ~$40k/year — a ~$100B annual US wage bill exposed to deflation.^[11] Globally the customer service workforce is on the order of 17M. The contact-center software market is already ~$48B and growing at 23%+ CAGR through 2032 — voice AI is the highest-growth wedge inside that envelope.^[8]

Adoption is past the experiment phase. 80% of contact centers already use some form of AI; 76% plan to boost AI investment in the next two years.^[6] Gartner's forecast — $80B of contact-center agent labor cost removed by conversational AI in 2026 — was made in 2022 and comes due this year.^[24] The buyer side is not the bottleneck — the bottleneck is whether the product can actually do the complex 70% reliably. That's what Leaping is selling.

The voice-agent slice specifically is the fastest-growing wedge inside that envelope: Grand View Research sizes the AI voice agents market at $2.54B in 2025, growing at a 39% CAGR to $35B+ by 2033.^[23] A 39% CAGR on a $2.5B base means the software market alone 14x's inside the fund's hold period — before counting the labor budget that converts to software spend as containment rates rise.