Provider Comparison Harness

High AI Agent system

A repeatable test rig that runs the same scripted scenarios through Vapi, Retell, and Bland and scores them side by side on latency, interruption handling, transcription accuracy, task completion, and cost. Turns provider selection into evidence instead of a vendor pitch.

Timeline 1-2 weeks

HMX Zone

ai agent system

High Agents system

Verified HMX-owned system details.

Timeline
1-2 weeks
Visual motif
Reasoning orbit
Live datum
A message is classified, noted, then handed to a human when needed.
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operating facts

Outcome

A clear, current recommendation for which voice provider fits this use case, backed by measured numbers rather than marketing.

Main risk

An unfair test (mismatched voices, models, or scenarios) produces a misleading 'winner'.

Prevention

Hold STT/TTS/LLM and scripts constant across providers, run multiple trials, and document every configuration difference.

Fallback

If results are too close or noisy to call, recommend a limited live pilot on the top two before committing.

system architecture

Provider Comparison Harness Architecture

a fixed scenario set with
each scenario through each
Vapi
Retell
Human Escalation
Agent Handoff
  1. 01a fixed scenario set with

    A repeatable test rig that runs the same scripted scenarios through Vapi, Retell, and Bland and scores them side by side on latency, interruption h...

  2. 02each scenario through each

    Run each scenario through each provider with matched STT/TTS/LLM settings where possible

  3. 03Vapi

    Vapi runs the bounded conversation step for Provider Comparison Harness while keeping tool use, transcripts, and escalation outcomes explicit.

  4. 04Retell

    Capture latency, barge-in behavior, transcript accuracy, task success, and per-minute cost per run

  5. 05Human Escalation

    If results are too close or noisy to call, recommend a limited live pilot on the top two before committing.

  6. 06Agent Handoff

    A clear, current recommendation for which voice provider fits this use case, backed by measured numbers rather than marketing.

how it is built

  1. 01Build a fixed scenario set (qualification, booking, objection, escalation) with expected outcomes
  2. 02Run each scenario through each provider with matched STT/TTS/LLM settings where possible
  3. 03Capture latency, barge-in behavior, transcript accuracy, task success, and per-minute cost per run
  4. 04Produce a comparison scorecard and a recommendation tied to the specific use case and volume

architecture notes

Architecture overview

Provider Comparison Harness uses a bounded agent handoff layer for AI Agents. A repeatable test rig that runs the same scripted scenarios through Vapi, Retell, and Bland and scores them side by side on latency, interruption h... The architecture connects a fixed scenario set with, vapi, retell, and agent handoff with an explicit control path.

  • Conversation layer: Build a fixed scenario set (qualification, booking, objection, escalation) with expected outcomes
  • Reasoning layer: Run each scenario through each provider with matched STT/TTS/LLM settings where possible
  • Tools layer: Vapi runs the bounded conversation step for Provider Comparison Harness while keeping tool use, transcripts, and escalation outcomes explicit.
  • Records layer: Retell connects calls, messages, calendar work, or CRM writes while hold STT/TTS/LLM and scripts constant across providers, run multiple trials, and document every configuration difference.
  • Escalation layer: A clear, current recommendation for which voice provider fits this use case, backed by measured numbers rather than marketing.

Data flow

  1. Build a fixed scenario set (qualification, booking, objection, escalation) with expected outcomes
  2. Run each scenario through each provider with matched STT/TTS/LLM settings where possible
  3. Capture latency, barge-in behavior, transcript accuracy, task success, and per-minute cost per run
  4. Produce a comparison scorecard and a recommendation tied to the specific use case and volume

Controls and fallbacks

  • An unfair test (mismatched voices, models, or scenarios) produces a misleading 'winner'.
  • Hold STT/TTS/LLM and scripts constant across providers, run multiple trials, and document every configuration difference.
  • If results are too close or noisy to call, recommend a limited live pilot on the top two before committing.

Tools

  • Vapi
  • Retell
  • Bland
  • Deepgram
  • ElevenLabs
  • OpenAI
  • Twilio

research basis

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