Avoma Review, Pricing & Alternatives (2026)

Avoma is a hosted AI meeting and revenue intelligence platform for sales and revenue teams. The company says it was founded in 2017 by Aditya Kothadiya, Devendra Laulkar, and Albert Lai, and publicly launched its AI meeting assistant in 2019. Avoma reported a $3 million seed round in 2020 and a $12 million Series A in 2021, bringing reported funding to $15 million. Its product includes meeting recording, transcription, summaries, scheduling, conversation intelligence, revenue intelligence, and CRM workflows. Avoma sells the service as SaaS, with paid recorder seats and free view-only access for collaborators. It does not offer a self-hosted or open-source edition. The company positions the product for teams that need meeting content connected to sales operations.

Avoma's typical workflow starts with a connected Zoom, Microsoft Teams, Google Meet, Webex, or GoToMeeting session. The AI Meeting Assistant records and transcribes the conversation, then generates summaries, action items, follow-up emails, and searchable meeting content. Users can apply templates, topics, playlists, and coaching criteria, or ask questions through Ask Avoma. Scheduler supports one-to-one and group booking, while Lead Router supports routing and round-robin assignment. CRM and dialer integrations send meeting information into sales systems. Teams can review calls, compare conversation patterns, monitor deal activity, and analyze pipeline information. API and webhook access is listed for Organization and Enterprise plans. The result is a meeting-centered layer around existing conferencing, CRM, and sales tools.

Avoma does not identify a specific underlying model or fixed model version. Its published capabilities include transcription, automated summaries, AI-generated emails, Ask Avoma, translation, configurable sources, and external service integrations. Product updates in 2026 added a Claude connector, email as an Ask Avoma source, MCP OAuth connections, pipeline trend and pipeline walk views, and ISO/IEC 42001 certification. These releases extend the product from meeting documentation into sales knowledge and pipeline analysis. Avoma presents the technology as a hosted service with configurable notes and topics. It does not present the product as an API for selecting or fine-tuning a public foundation model. Customers choosing Avoma are buying a managed workflow rather than direct control over model selection, inference settings, or training pipelines.

Avoma's Startup or Essentials plan costs $19 per paid recorder seat per month with annual billing, or $29 with monthly billing. It includes unlimited AI Meeting Assistant use and one-to-one scheduling. The current pricing page lists up to 25 paid recorder seats, although a separate help article lists 20. Organization costs $29 annually billed per month, or $39 with monthly billing, and adds custom notes, group scheduling, limited conversation intelligence, automations, translation, API access, and webhooks. Enterprise costs $39 per seat monthly with annual billing and requires 10 seats. Conversation Intelligence and Revenue Intelligence each cost $29 annually billed per month, while Lead Router costs $19. Viewers are free, recording storage is described as unlimited, and uploads have plan-based monthly limits.

Avoma focuses more narrowly on meeting-centered sales intelligence than a complete sales system. Close combines CRM records with native email, calling, SMS, and sales automation, while Gong centers on revenue intelligence and conversation analysis. Fireflies.ai and Otter.ai concentrate more heavily on recording, transcription, and meeting summaries. Avoma can become more expensive when teams add conversation intelligence, revenue intelligence, Lead Router, or Enterprise controls. Published Startup seat limits differ across Avoma pages, and customers remain responsible for recording consent and lawful use. The company says customer data is not used to train its models. Sales teams with an existing CRM should pick Avoma when meeting intelligence, scheduling, and pipeline context matter more than native CRM engagement.