Bland AI vs Fireflies AI

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

Bland AI has raised more in total funding at $22M, compared to Fireflies AI's $19M — a gap of $3M. Combined, the two companies have completed 2 known funding rounds.

Fireflies AI leads with an Awaira Score of 82/100, while Bland AI sits at 40/100. That 42-point gap reflects real differences in funding, scale, and traction — it's not a vanity metric.

Bland AI was founded by Isaiah Miller in 2023. Fireflies AI was founded by Krish Ramineni in 2016. Visit each company's profile on Awaira for a full founder biography.

Bland AI: Bland AI provides an AI phone call automation platform that enables businesses to deploy human-sounding AI agents for inbound and outbound telephone interactions at scale. The platform handles appointment scheduling, customer support, debt collection, and sales qualification calls with voice agents that adapt dynamically to conversation flow.\n\nThe company raised approximately 22 million USD and has demonstrated early traction with clients in healthcare, real estate, financial services, and logistics, sectors where phone-based customer contact remains operationally intensive. Bland differentiates through low-latency voice synthesis and the ability to build custom telephony workflows without engineering resources.\n\nAutomated voice AI sits at the intersection of call center outsourcing and conversational AI, a market historically measured in tens of billions of dollars annually. The shift toward AI-native phone infrastructure represents a fundamental change in how businesses handle call volume, and Bland is positioned at the early edge of that transition alongside competitors including Retell AI, Vapi, and Synthflow. 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 7 years of extra runway. Bland AI didn't arrive until 2023. In AI, that kind of head start means more training data, deeper customer relationships, and a bigger talent moat.

Bland AI has about 1-50 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 Bland AI 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.