Speak AI vs Retell AI:
voice agents plus
the analysis layer.

What Retell AI does well

Retell AI is a Y Combinator-backed voice agent platform that has earned its reputation. Its proprietary orchestration delivers roughly 600ms response latency, which makes phone conversations feel natural, and it powers over 50 million calls a month for contact centers in healthcare, insurance, logistics, and financial services (as of mid-2026). It holds SOC 2 Type II certification, offers HIPAA and GDPR compliance, integrates with Twilio, Five9, Genesys, Amazon Connect, HubSpot, and Salesforce, and its post-call analysis returns transcripts, sentiment scores, and custom extraction fields for every call its agents handle. For an engineering team building a high-volume phone automation product, Retell is a legitimately strong choice, and it earned a 4.8/5 on G2.

Where a phone agent stops being enough

Retell is a component: it runs the call and reports on the call. It cannot transcribe the recorded interview on your laptop, the Zoom meeting your team had yesterday, or the customer calls sitting in your old phone system. Speak AI is the layer above the call: multimodal analysis that reads the words, the tone of voice, the emotion in voice, and, when there is video, the body language and what’s on screen. That full context is the categorical difference between a call log and a system of record. A call scoring rubric, a coaching workflow, or a research synthesis needs all three layers, and it needs them for every conversation, whichever tool carried it.

Voice agents without an engineering project

Speak AI includes AI音声エージェント you launch from your workspace with no code, and every agent call lands directly in the same archive as your meetings and uploads, already transcribed and analyzed. Retell’s developer API goes deeper on custom telephony engineering: fine-grained conversation flows, IVR navigation, batch campaigns at contact-center volume. If you have engineers and a phone-automation product to build, that depth matters. If you want an agent answering calls this week, with the analysis included, you do not need the engineering project.

Predictable pricing vs per-minute stacking

As of August 2026, Retell prices per minute: its published range is $0.07 to $0.31 per minute all-in, assembled from voice infrastructure at $0.055/min, text-to-speech from $0.015 to $0.04/min, an LLM from $0.003 to $0.16/min, and telephony around $0.015/min, plus monthly line items for phone numbers, extra concurrency, and add-ons like knowledge bases and PII removal. It is fair pricing for infrastructure, and a $10 signup credit lets you test it, but the total is hard to predict before you know your volume. Speak AI offers a trial and flat subscription plans, with transparent pricing that does not stack per-minute charges.

Better together: run the calls, then own the context

These platforms are often used together. Teams run high-volume real-time calls on Retell, then bring recordings into Speak AI for post-call analysis, compliance review, coaching, and research synthesis alongside every other conversation the company has. Because Speak AI keeps transcript, audio signal, and screen content together, teams build custom applications on top of it: dashboards, call scoring rubrics, research coding, and reporting, through the API or the MCP server. That is context engineering: turning every conversation into contextual knowledge your tools and assistants can actually use.