Evaluation cycles longer than the project
Enterprise voice AI often arrives as a process rather than a product: discovery calls, scoping, a solutions architect, a pilot, procurement, security review. At genuine enterprise scale that process exists for good reasons. It is a poor fit when the question is whether a voice agent can handle your appointment reminders, and you would like to know this month. Evaluation cycles measured in quarters mean most teams never reach the part where they learn something real.
Sign up and launch it yourself
Persistence is self-serve from the first minute. Create an account, build an agent, put it on a real phone number, and call it — without booking a meeting. Simple use cases start from a single prompt. Complex ones get a visual flow builder with branching logic and fallback routes, on a canvas your team can work in together with role-based access separating who edits from who publishes.
Start from a working agent
Starting from an empty canvas is its own tax. Prebuilt templates cover the common shapes — scheduling, intake, order status, qualification, reminders — so the first version is something you edit rather than something you architect. Most teams get to a working agent in an afternoon, which is roughly when the interesting questions start.
Prove it on real calls before committing
Simulation runs your agent against hundreds of scenarios including the awkward ones: mid-sentence pauses, interruptions, accents, callers who change their mind halfway through. You see how it performs before a customer does and before you have signed anything. Versioning is automatic, so iterating is cheap and reverting is instant.
Numbers you can take to whoever signs off
Every conversation is transcribed, scored and searchable, with containment, conversion, sentiment and latency tracked by default. That matters for the internal conversation as much as the operational one: you can show what the agent handled and what it escalated, on your own call volume, rather than describing potential from a vendor deck.
Grounded answers and real actions
Connect your documentation and databases so answers come from your source of truth, not from plausible-sounding guesses. Mid-call the agent can transfer to a human with context attached, book a slot, hit an API or update a record — the difference between deflecting a call and completing the task the caller rang about.
Scale on your own timeline
When inbound is working, go outbound: upload a contact list or trigger via API and run thousands of concurrent calls for reminders, qualification, surveys or collections, scheduled to respect time zones and dialling windows. The same agent deploys across phone, web chat and SMS from one build.
Keep a human in the loop where it matters
Self-serve does not have to mean unsupervised. Live call supervision lets a person watch conversations as they happen and step in when a call warrants it, which is what makes it reasonable to put an agent on a line that matters before you fully trust it.
No contract standing in the way
$10 in free credits to start, then you pay for what you use. No annual commitment, no seat minimums, no procurement cycle between you and a working agent. If it does not suit your call types you will know in a week, which is the outcome a long evaluation was supposed to buy you anyway.
Key takeaways
- Persistence is self-serve: create an account, build an agent, put it on a real number and call it, without a discovery call or procurement cycle.
- Prebuilt templates cover common call types, so the first version is something you edit rather than architect from an empty canvas.
- Simulation proves the agent on hundreds of scenarios before a customer hears it, and analytics give you real numbers to show whoever signs off.
- Pay-as-you-go from $10 in free credits, with no annual commitment or seat minimums — if it does not fit your call types you know within a week.
