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AssemblyAI

API-based speech transcription and analytics

Overview

AssemblyAI provides an API-driven Speech AI platform that converts audio and video into text and insights. Its models handle automatic transcription and add-ons like speaker diarization, sentiment analysis, and PII redaction, all delivered through scalable API endpoints so customers can integrate transcription and audio analytics into their own apps. Unlike many competitors, AssemblyAI emphasizes a combination of high accuracy, broad capabilities (including privacy-focused features), and ongoing model improvements from a research-driven team, with a subscription-based pricing model for access and data processed. The company aims to help businesses unlock voice data by turning speech into actionable information that can power products and services across tech, media, and enterprise sectors.

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About AssemblyAI

Simplify's Rating
Why AssemblyAI is rated
B-
Rated B on Competitive Edge
Rated B on Growth Potential
Rated C on Differentiation

Industries

Data & AnalyticsEnterprise SoftwareAI & Machine Learning

Company Size

51-200

Company Stage

Series C

Total Funding

$113.1M

Headquarters

San Francisco, CA

Founded

2017

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What believers are saying

  • October 2026 TTS-1 launch gives AssemblyAI a full voice-agent stack on one API key.
  • LLM Gateway bundles 50+ models, reducing developer switching costs and expanding usage.
  • Roadmap shows EU processing and unlimited concurrency, meeting regulated enterprise demand now.

What critics are saying

  • Tesseract Systems sued AssemblyAI on May 27, 2026; patent litigation costs loom.
  • ElevenLabs, Cartesia, and Inworld undercut pricing and benchmarks, eroding AssemblyAI's voice moat.
  • AssemblyAI lacks an open-weights or on-prem product, leaving enterprise deal flow exposed.

What makes AssemblyAI unique

  • October 2026 launches tied transcription, LLM routing, and TTS into one API.
  • AssemblyAI-TTS-1 launched October 27, 2026 with 4,000+ voices and six languages.
  • Voice Standard Bench on October 13, 2026 ranks 50+ models on real transcripts.

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Funding

Total Funding

$113.1M

Meets

Industry Average

Funded Over

5 Rounds

Series C funding is usually for startups that are doing well and are looking for more money to fuel major growth, such as acquiring other companies, expanding into global markets, or launching new product lines. Investors typically include larger venture capital firms and private equity.
Series C Funding Comparison
Meet Average

Industry standards

$50M
$50M
$50M
$62M
$100M

Benefits

  • Competitive Salary + Bonus
  • Equity
  • 401k
  • 100% Remote team
  • Unlimited PTO
  • Premium medical, vision, & dental care
  • $1K budget for your home office setup
  • New Macbook Pro (or PC if you prefer)
  • 2x/year company paid team retreat

Growth & Insights and Company News

6 month growth

-3%

1 year growth

-4%

2 year growth

-3%
Banca di Bologna
Nov 3rd, 2026
AssemblyAI and Cartesia split voice agents by layer.

AssemblyAI and Cartesia split voice agents by layer. BitRss Crypto News 5 hours ago 58 AssemblyAI and Cartesia now compete across speech synthesis, transcription and orchestration, with different language coverage, pricing and benchmarks. (Read More) BankBit shares this Content always with CC License Screenshot generated in real time with SneakPeek Suite

MarkTechPost
Oct 29th, 2026
AssemblyAI ships AssemblyAI-TTS-1: A $15 per 1M character text-to-speech API for voice agents.

AssemblyAI ships AssemblyAI-TTS-1: A $15 per 1M character text-to-speech API for voice agents. October 29, 2026 AssemblyAI has released AssemblyAI-TTS-1, its first text-to-speech model, now generally available. The AssemblyAI-TTS-1 text-to-speech API targets voice agents running on live phone calls. In that setting, latency and pronunciation decide whether a caller stays on the line. Pricing is $15 per 1M characters, with no annual contract and no concurrency tier to buy. For developers already using AssemblyAI speech-to-text, it closes the voice loop with one vendor. Tl;dr. * Size: It is a hosted API model. * Runs on: AssemblyAI's cloud only, in the US (Marktechpost LLC.-east-1) or EU (eu-north-1). No open weights or on-prem option. Any client with HTTP or WebSocket works. * Performance: Ties ElevenLabs v4 on entity accuracy in AssemblyAI's tests, at under 1/5 of its price. * Best: 47 ms median time to first byte across 6 models in AssemblyAI's API test (self-reported). * Worst: 159 ms median streaming latency on Cekura's independent benchmark, 8th of 19 timed models. * Bottom line: * Best: $15 per 1M characters with unlimited concurrency. * Worst: no SSML, speed control, pronunciation dictionaries or emotion tags yet. What is AssemblyAI-TTS-1? AssemblyAI-TTS-1 is a streaming text-to-speech model from AssemblyAI that turns agent replies into speech for live calls. It was trained on millions of hours of audio, including real conversational data. Most TTS models represent audio as discrete tokens. AssemblyAI says TTS-1 operates on continuous audio representations instead. The AssemblyAI claims this improves realism and cuts time to first spoken audio. The launch includes a library of 4,000+ voices and instant voice cloning. A clone needs a short recording and a confirmation of the speaker's permission. The clone in the launch post used 24 seconds of audio. Six languages are supported at launch: English, Spanish, French, German, Italian and Portuguese. How do developers integrate AssemblyAI-TTS-1? There are 3 interfaces: an HTTP API, a WebSocket API and an OpenAI-compatible route. The WebSocket session keeps one connection per conversation and accepts a cancel message for barge-in. Output is mono PCM, mu-law or A-law, at 8 kHz to 48 kHz. 24 kHz PCM is the native format; telephony stacks can request 8 kHz mu-law directly. Word timestamps are included. AssemblyAI also published LiveKit and Pipecat reference agents. How does AssemblyAI-TTS-1 perform on benchmarks? AssemblyAI tested TTS-1 against 5 models on 4 English sets, using 50 matched cloned voices. All figures below are self-reported, from an eval dated October 28, 2026. * Entity accuracy (580 hard targets such as phone numbers and codes): 93.7%, vs ElevenLabs v4 93.6%, Cartesia Sonic 3.6 82.5%, ElevenLabs Flash v2.5 68.0%. * Word accuracy: 99.0% on Seed-TTS and LibriSpeech sentences. * Predicted MOS: 3.85, behind Inworld TTS-2 Flash at 3.88 and ahead of Sonic 3.6 at 3.82. * Median time to first byte: 47 ms. Flash v2.5 took 119 ms, Sonic 3.6 143 ms, Inworld TTS-2 Flash 244 ms. * Other: 85.5 TTSDS prosody score and 0.64 speaker similarity for cloned audio. Independent results are more mixed. On Cekura's benchmark of 27 models, TTS-1 scored 81.5% reading accuracy and 4.50 naturalness. Its median streaming latency, timed from the last word sent, was 159 ms. Inworld TTS-2 Flash posted 45 ms and 93.2% accuracy there, at the same $15 price. AssemblyAI also cites a 1.7% word error rate on Coval's leaderboard. It reports a top-10 debut in Artificial Analysis' controlled-voice arena. How does AssemblyAI-TTS-1 compare with ElevenLabs, Cartesia and Inworld? Cartesia's range divides each plan price by its credits, at 1 credit per character. What does AssemblyAI-TTS-1 cost? Pricing is per input character, including spaces and punctuation, at $15 per 1M. Every voice, cloning, word timestamps and EU processing come at that same rate. There are no per-voice fees, concurrency fees or minimums. AssemblyAI calls it the lowest-priced frontier TTS model for voice agents. However, Inworld TTS-2 Flash also lists $15 per 1M on demand, falling to $7 on paid plans. The sharper difference is concurrency: Inworld's on-demand tier allows 5 concurrent requests. Key takeaways. * AssemblyAI-TTS-1 is AssemblyAI's first text-to-speech model, built for live voice agents. * It costs $15 per 1M characters, with unlimited concurrency and no contract. * Self-reported: 93.7% entity accuracy and 47 ms median time to first byte. * Cekura measured 159 ms streaming latency and 81.5% reading accuracy. * Missing at launch: SSML, speed control, pronunciation dictionaries and emotion tags. Need to partner with Marktechpost LLC. for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with Marktechpost LLC. Michal Sutter is a data science professional with a Master of Science in Data Science from the University of Padova. With a solid foundation in statistical analysis, machine learning, and data engineering, Michal excels at transforming complex datasets into actionable insights.

TokenPost
Oct 13th, 2026
AssemblyAI launches voice benchmark to cut LLM workload costs.

AssemblyAI launches voice benchmark to cut LLM workload costs. Voice Standard Bench compares more than 50 models across quality, response time and price for transcript-processing tasks ranging from 30 seconds to 60 minutes. Published Oct 13, 2026, 5:31 PM EDT AssemblyAI launched Voice Standard Bench on Oct. 13, 2026, comparing more than 50 large language models for voice-product workloads so developers can match model size and cost to each transcript task. The benchmark evaluates information extraction, summarization, text correction and dictation cleanup across transcripts lasting about 30 seconds, two minutes, 15 minutes and 60 minutes. Results use a 0-to-100 quality scale and include each model's cost per hour of audio and median response time. Voice applications often send speech-to-text transcripts to an LLM for cleanup, classification, structured extraction or summaries. AssemblyAI's approach is to select models based on the task and transcript length instead of using one model throughout a pipeline. AssemblyAI's LLM Gateway provides access to more than 50 models through one OpenAI-compatible application programming interface. It uses the same API key as the company's speech-to-text service. Listed rates as of Oct. 8, 2026, included $0.10 per 1 million input tokens and $0.50 per 1 million output tokens for Qwen3.5 4B Fast. Gemma 4 31B was listed at $0.14 for input and $0.40 for output, while GPT OSS 20B was priced at $0.07 and $0.30. Nemotron Lightning 3.5 30B A3B was listed at $0.05 for input and $0.20 for output. One example modeled 10,000 monthly support calls lasting about 15 minutes each, with 3,200 input tokens and 300 output tokens per call. Estimated monthly costs ranged from $141 for Claude Sonnet 5 to $4.70 for GPT-6 Luna. At 1 million calls per month under the same assumptions, projected costs were $14,100 for Claude Sonnet 5, $470 for GPT-6 Luna and $568 for Gemma 4 31B. "Most of it doesn't need one," Kelsey Foster said, referring to frontier models. The benchmark counts format failures, refusals, timeouts and errors in its quality scores rather than measuring only successful responses. Companies can test the open-source benchmark using their own voice transcripts, task instructions and specialized terminology. Global routing carries no markup, while routing within the United States or European Union costs 10% more. Claude Sonnet 4.5 on LLM Gateway is scheduled to retire on Nov. 30, 2026. Simon Yoon. Simon Yoon reports on blockchain technology for TokenPost. Send corrections or tips to [email protected].

AssemblyAI
Sep 12th, 2026
Announcing our $50M Series C to build superhuman Voice AI models

We're excited to share that we’ve raised $50M in Series C funding led by Accel, our partners that also led our Series A, with participation from Keith Block and Smith Point Capital, Insight Partners, Daniel Gross and Nat Friedman, and Y Combinator.

AssemblyAI
Jan 9th, 2025
Dev.to x AssemblyAI: Winter Speech-to-Text Challenge Winners

Last month, AssemblyAI, Inc. partnered with developer community hub Dev.to to host a winter hacking challenge!

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