Research

Pushing voice AI
forward.

Advancing the state of conversational voice AI for business. Our research team works on making AI phone agents faster, more natural, and more reliable.

Research areas

Four frontiers we're building on.

Every conversation is a research problem. Here's where we're focused right now.

Conversational AI for Business

Building AI that handles the nuances of real business phone conversations including accents, interruptions, background noise, and complex multi-turn dialogues.

Real-Time Voice Synthesis

Developing low-latency voice models that sound natural and maintain consistent personality across thousands of concurrent conversations.

Context-Aware Response Generation

Training models to dynamically draw from business-specific knowledge bases like menus, services, schedules, and FAQs during live calls.

Multilingual Understanding

Expanding language support with auto-detection, code-switching, and dialect awareness to serve diverse caller populations.

Publications

Read our latest work.

Open papers, benchmarks, and technical write-ups from the OmniGreet Research team.

February 2026

Benchmarking Voice AI Latency in Real-World Business Call Scenarios

OmniGreet Research Team

We measured end-to-end response latencies across 100K+ production calls and identified the key bottlenecks affecting conversational quality.

Read paper

January 2026

Domain-Specific Fine-Tuning for Vertical Voice Assistants

OmniGreet Research Team

How targeted fine-tuning on industry-specific call data improves appointment booking accuracy by 34% compared to general-purpose models.

Read paper

Join our research team.

We're hiring researchers and engineers who want to push the boundaries of conversational voice AI.

No credit card neededLive in under 24 hoursCancel anytime