First, match the provider to the call job

Compare OpenAI Realtime and Replicant for AI phone agents, then match channels, workflows, and deployment models to your call flow.

Both profiles checked 2026-09-04.

Use the table below to compare each provider’s documented scope.

Before you decide

OpenAI Realtime vs Replicant: buying questions

How should I compare OpenAI Realtime and Replicant pricing?

OpenAI Realtime: Token-based API pricing for text, audio, and image modalities; audio input/output rates are published per million tokens. Replicant: Not publicly documented; the listed pricing page is an ROI calculator rather than a product rate. Ask both vendors to quote the same expected workload, required channels, and implementation scope. Include required subscriptions and usage charges before comparing the total; the listed starting prices alone may cover different work.

Can OpenAI Realtime and Replicant use my existing data?

The recorded knowledge and data sources for OpenAI Realtime include Not publicly documented. For Replicant, they include Not publicly documented. Ask each provider to demonstrate access for the exact systems you use, with permissions, freshness, and failure behavior. A source missing from this directory is not proof that a provider cannot support it.

What should I test in a OpenAI Realtime vs Replicant pilot?

Use the same representative calls, approved instructions, and escalation rules in both pilots. How does it handle interruption and uncertainty? Which actions can it complete, and which require approval? What context reaches a human during transfer? Record conversation quality, completed tasks, human handoffs, and total cost in the buyer worksheet. Check these specific cautions before launch: OpenAI Realtime: Not a turnkey contact center. Implement telephony operations, identity, tools, monitoring, evaluation, retention, and escalation. Replicant: Scope claims to trained call types. Confirm containment definition, transfer behavior, languages, deployment, and price tier.

Record your requirements and pilot results in the buyer worksheet →

Swipe or scroll the table to see every column.

Features, pricing, and fit
CriterionRealtime APIReplicant
Provider typeNative realtime multimodal model APIEnterprise contact-center voice AI
Best fitProduct and engineering teams building a spoken application around a realtime model instead of a packaged contact-center product.Contact centers automating defined call types with historical conversations, business logic, and controlled escalation paths.
Key capabilitiesaudio-to-audio conversation; WebRTC; WebSocket; SIP; toolsinbound call automation; contact-center integration; human escalation; analytics
Team sizesstartup; mid-market; enterprise; developerenterprise; contact centers
Call surfacesWebRTC; WebSocket; SIP; API / SDKphone / PSTN; API / SDK
Voice stackNative audio input/output with tool callingCascaded speech pipeline
TelephonySIP connection; carrier integration remains buyer responsibilityNot publicly documented
Call controlsNot publicly documentedNot publicly documented
LanguagesNot publicly documentedNot publicly documented
IntegrationsNot publicly documentedNot publicly documented
Knowledge and dataNot publicly documentedNot publicly documented
Pricing modelToken-based API pricing for text, audio, and image modalities; audio input/output rates are published per million tokens.Not publicly documented; the listed pricing page is an ROI calculator rather than a product rate.
Pricing signalGPT-Realtime audio $32 per million input audio tokens and $64 per million output audio tokens.Custom enterprise tiers; no public rate.
Free plan or trialNot publicly documentedNot publicly documented
What stands outGPT-Realtime accepts and returns audio directly, while the Agents SDK supplies transport helpers plus tools, guardrails, handoffs, and session history.Replicant’s Learn–Replicate–Test–Deploy–Improve workflow starts with human-call analysis and combines LLMs with code-based guardrails, simulation, A/B tests, monitoring, and escalation.
ConsiderationsNot a turnkey contact center. Implement telephony operations, identity, tools, monitoring, evaluation, retention, and escalation.Scope claims to trained call types. Confirm containment definition, transfer behavior, languages, deployment, and price tier.

Realtime API: fit and scope

Product and engineering teams building a spoken application around a realtime model instead of a packaged contact-center product.

GPT-Realtime accepts and returns audio directly, while the Agents SDK supplies transport helpers plus tools, guardrails, handoffs, and session history.

Replicant: fit and scope

Contact centers automating defined call types with historical conversations, business logic, and controlled escalation paths.

Replicant’s Learn–Replicate–Test–Deploy–Improve workflow starts with human-call analysis and combines LLMs with code-based guardrails, simulation, A/B tests, monitoring, and escalation.

Verify current pricing, limits, security, and required integrations directly with each provider before purchasing.

Evaluate language support in real calls

Test recognition, speech quality, interruptions, language switching, tool use, and human transfer with your own calls in the required language. Availability can vary by model, plan, and phone route.

DocsBot documents multilingual voice workflows and Japanese support. Verify the exact voice, phone path, and transfer behavior in your pilot. Review DocsBot language information ↗

Other providers’ language claims reflect cited vendor material; confirm Japanese and other required languages directly with each provider.

Listing does not imply endorsement or a performance guarantee. This directory is published by DocsBot. Editorial policy

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