EliteDial: AI voice platform built inside a collections agency

I run a collections agency. Collections is one of the most heavily regulated kinds of calling there is: calling windows by the consumer's time zone, do-not-call lists, required disclosures, identity checks before any account detail is discussed, and an audit trail for every call.

Off-the-shelf dialers weren't built for that compliance load, and they weren't built for AI agents working alongside human collectors. So I built my own.

EliteDial is a full-stack dialer and AI voice platform. Human collectors and AI voice agents work the same lists, campaigns and compliance rules from one console.

The operations dashboard shows live calls, agent availability, running campaigns, connect and right-party contact rates, and the full contact pipeline. It updates in real time without anyone refreshing the page. Agents move between available, busy, wrap-up and offline, and supervisors see it as it happens.

Manual: the agent clicks to dial.

Preview: the agent sees the account before the call is placed.

Progressive: the next contact is dialed as soon as an agent frees up.

Predictive: dials ahead of agent availability, with abandon-rate guardrails and answering machine detection.

Each campaign has its own pacing, concurrency cap and routing: human only, AI only, or AI with overflow to a person. AI agents can live-transfer a call to a human collector mid-conversation. Contact lists import from CSV or JSON, with duplicates and do-not-call numbers suppressed on the way in, and contacts are reserved so no two agents dial the same person.

Calling windows (8 AM to 9 PM) enforced in each contact's own time zone.

Do-not-call enforcement that fails safe: if the check errors, the call is denied.

Consumer-protection flags and a full audit trail of every call event and disposition.

Local presence: caller IDs matched by area code, state and region, with health scoring and rotation so numbers don't burn out.

Most collection floors QA a small sample of calls. EliteDial runs automated compliance and QA scoring on every recorded call: required disclosures, identity verification, third-party disclosure, script adherence, accuracy of payment terms, and tone. Anything flagged goes to a review queue, where a supervisor can open the call and confirm or override the finding.

Built in-house at my agency, for our own calls.

Proven on live production call volume. Every rule and workflow was tested against real accounts, not demos.

Productized. The engine now powers a multi-tenant version for other operators and AI voice companies. Each client brings its own AI agent, and connecting a new one is configuration, not new code.

See it at elitedial.app.

TypeScript, Node.js, Next.js, PostgreSQL (Supabase), Prisma, Socket.IO, Recharts, Docker, with SignalWire for telephony and Retell for AI voice.

I build the same kind of system for other teams: AI voice agents, dialing, and the compliance and QA layer around them. Start with a Voice Agent Audit, or go straight to the AI Voice Agent Pilot: one agent live on real calls in 10 business days.