AI Employee Calling & Reporting Platform
Autonomous voice agents that call, converse and report — at scale.
Problem
Operations teams spent hours on repetitive calls — follow-ups, verifications, reminders — with no structured record of what happened or what to do next.
Scale
Designed to run thousands of concurrent AI voice interactions and turn each one into structured, queryable business intelligence.
Architecture
Telephony ingress feeds an AI orchestration layer that routes to LLM providers via a cost-aware model router. Conversations are transcribed, structured with schema-constrained extraction, and pushed into a reporting store with analytics.
My Role
Founder, Architect & Lead Engineer — owned system design, model routing, extraction schema and reporting.
Business Impact
Converted unstructured phone conversations into structured operational intelligence, removing manual calling and reporting workloads.
Result
A production-grade blueprint for AI voice operations — calling, understanding and reporting as one automated pipeline.
Engineering decisions
- Provider-agnostic model router to optimize cost and latency per call type.
- Schema-constrained extraction so every call yields consistent, queryable fields.
- Separation of conversation, extraction and reporting into independent stages.
Key challenges
- Keeping latency low enough for natural conversation while routing across providers.
- Guaranteeing structured output reliability from probabilistic models.