Voiceflow vs Fireflies AI

Fireflies AI has a disclosed valuation of $1B, while Voiceflow's valuation is not publicly available, making a direct size comparison difficult. Fireflies AI employs 150 people.

Voiceflow has raised more in total funding at $39M, compared to Fireflies AI's $19M — a gap of $20M. Combined, the two companies have completed 4 known funding rounds.

Fireflies AI leads with an Awaira Score of 82/100, while Voiceflow sits at 60/100. That 22-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Voiceflow was founded by Braden Ream in 2019. Fireflies AI was founded by Krish Ramineni in 2016. Visit each company's profile on Awaira for a full founder biography.

Voiceflow: Voiceflow provides a collaborative platform for designing, building, and deploying conversational AI agents across web chat, voice interfaces, and messaging channels. The platform abstracts the complexity of LLM orchestration, intent recognition, and multi-turn dialogue management behind a visual workflow builder accessible to both technical and non-technical teams.\n\nThe company raised approximately 50 million USD and serves thousands of product teams at companies including Google, JP Morgan, and Walmart that build and iterate on conversational products. Voiceflow has established a two-sided ecosystem with agent templates and a growing marketplace of integrations that increase platform stickiness and reduce customer churn.\n\nThe market for no-code and low-code conversational AI tooling is expanding rapidly as every business-facing product team is now expected to ship an AI assistant. Voiceflow occupies a distinct position between pure developer frameworks like Rasa and enterprise-locked platforms from Salesforce and ServiceNow, giving it a broad addressable market among the millions of product teams globally who need to ship dialogue experiences without building infrastructure from scratch. Fireflies AI: Fireflies AI develops conversation intelligence software that records, transcribes, and analyzes meetings across multiple platforms including Zoom, Google Meet, Microsoft Teams, and Slack. Founded in 2016, the company specializes in extracting actionable insights from meeting audio through automatic transcription and AI-powered analysis. The platform identifies key topics, generates meeting summaries, tracks action items, and surfaces relevant discussion points for sales, customer success, and business intelligence teams. Fireflies AI competes in the growing conversation intelligence market alongside platforms like Gong, Chorus, and Otter.ai, differentiating through integration breadth and accessibility. The company has raised $19M in total funding and achieved a $1.0B valuation, indicating significant market validation. Operating at Series A stage, Fireflies AI targets mid-market and enterprise customers across sales, customer support, and operations. The platform emphasizes ease of use and integrations with existing business tools. Notable use cases include sales call analysis, customer meeting documentation, and compliance recording. The company uses natural language processing and machine learning to improve transcription accuracy and insight generation. Fireflies AI's growth trajectory reflects broader adoption of conversation intelligence tools in remote and hybrid work environments where asynchronous meeting review has become standard practice. Fireflies AI offers platform-agnostic conversation intelligence with deep integrations across major communication tools, enabling meeting analysis at scale.

Fireflies AI got there first, launching in 2016 — that's 3 years of extra runway. Voiceflow didn't arrive until 2019. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Voiceflow has about 50-200 employees; Fireflies AI has about 150. A bigger team usually means more revenue or heavier VC backing, but in AI, small teams can build at massive scale.

Yes — they're direct rivals. Both Voiceflow and Fireflies AI compete in AI Agents, targeting many of the same buyers. If you're evaluating one, you should be looking at the other.