You've built the right wedge: not inbound support, not robo-dial volume, but the operational calls businesses must make to get work done. This page is my product thesis for what compounds on top of that wedge, six concepts, built the way I'd run product at AZcare. I came to Cisco through the BabbleLabs acquisition; consider this my application, in the only format that matters.
The major platforms are racing to turn your own meetings into work. None can reach the operational calls a business must place into other organizations' phone systems. That is the whitespace, and here is the wedge into it.
Not answering calls, placing them, into other organizations' IVR trees: pressing the right menus, surviving hold, passing verification, extracting the outcome. Operational work businesses do by the millions, entirely by phone, with no API and no transcript to mine.
Each completed call extracts structured knowledge and writes it back as a typed, confidence-scored graph. The next call starts smarter. The moat is not the calling; it is the accumulated map of the phone-based world that no competitor can buy.
Voice models are rented; everyone has them. What compounds is what only you can accumulate: the operational map of the phone-based world, and the loop that runs on it.
Before dialing, the agent already knows the counterparty: not just the IVR tree and verification requirements, but the payer's behavior, that it denies modifier-25 on first pass 79% of the time but reverses 80% on appeal, that its hold triples after 2pm. Every completed workflow writes this back. This behavioral model, the Genome, is the asset nobody else can accumulate.
Claim status requires member ID + provider NPI + TIN. Fastest path: menu 2 → 4, say "claims status" at the prompt. Average hold 14 min; best window Tue to Thu, 7 to 9am PT. If stalled past 20 min, the fax escalation path resolves in 1 business day.
Monday 8am. Every queued claim is scored with a forward-looking forecast: LIKELY APPROVE, LIKELY DENY, EXPECT ALREADY PAID, each with a recommendation to CALL, SKIP, or FIX FIRST. The system preempts: it flags the claim that will deny for a missing modifier before you waste the call, and skips the one a remittance feed already shows as paid. The highest-value call is the one you never place.
Mid-call, a payer demands something new, a rendering-provider taxonomy code no prior call required. A scripted agent fails here and escalates to a human. Otto instead recognizes the novel requirement, handles it on the call, and the system writes a new playbook rule on the spot: "Meridian now also requires the taxonomy code at verification." Every future call pre-loads it and sails through the wall that stopped the first one.
Any competitor can wire an agent to a fixed script. That script degrades the instant a counterparty changes something. A system that rewrites its own playbook gets stronger with every change it encounters, and because the learning pools across customers, the density no one else can match is exactly what makes each call smarter. This is the difference between brittle RPA and a system that improves itself.
The line for the buyer: your team stops re-learning each payer's new rules by getting burned. The first call catches the change; every call after is immune.
Filing appeals is not new; every billing shop does it, and denial-management tools template the letters. The innovation is what decides the appeal. Traditional tools use static rules: "modifier-25 denial, send template." Ours uses the Genome, so it knows that Meridian reverses 80% of these but Atlas only 31%. We do not appeal everything. We appeal what the data says will win, for that specific payer, from reversal behavior no one else has because no one else makes the calls.
This is not a standalone feature bolted on; it is the proof that the data moat pays in dollars. Because we make every call, we learn each payer's true reversal behavior, and that is what lets us tell a biller which denials to fight and file them on the spot. A competitor can file appeals. They cannot know Meridian reverses 80% and Atlas 31% without the call volume we have. The graph is the moat; the appeal engine is where the moat becomes revenue.
The pricing unlock: because we can score recoverable value, we can charge a percentage of recovered revenue, aligning price directly with dollars delivered. No one without the per-payer reversal data can price that risk.
An AZ agent dials a payer, starts navigating the IVR, and detects an AI agent on the other end. The call flips from voice theater to structured protocol: verification tokens exchanged, claim status returned, done in seconds. Voice remains the universal fallback; protocol becomes the fast path. First-time counterparty agents route through a human trust gate.
A COO glances at the board mid-quarter: completion rate ticking up, hold-hours absorbed piling into the hundreds, one counterparty degrading two weeks running, with the system already proposing the fix. The dashboard is the sales artifact: value visible live, renewal conversation already won.
Otto is the calling agent at the center of this. This is not a slide or a mock: Otto places a real phone call, navigates the payer IVR, survives hold, passes verification, and the Counterparty Graph builds itself on screen from the live transcript while the Completion Pulse ticks. The concepts you just read, running end to end, driven by one agent you can point at any payer.
AZcare's hard problems are the ones I've spent a career shipping through: speech at production scale, AI that survives real phone systems, governance that clears enterprise procurement, and platforms that turn calls into structured outcomes.
20+ customer conversations in 30 days. Which vertical's Graph is densest value first: payers, banks, or government? Which workflow is the land, which is the expand?
Per-completion pricing anchored to hold-hours absorbed, with SLA-backed tiers the Predictor makes possible. Value pricing, not seat pricing.
Data network effects with per-customer privacy walls, designed from day one. The moat gets architected now or never.
TCPA, HIPAA, consent, recording laws, adversarial testing of voice agents. The compliance posture that turns pilots into enterprise contracts.