The AI layer that hears every earnings call - and turns Wall Street's spoken word into searchable, cited intelligence.
Every quarter, thousands of companies hold earnings calls within the same handful of weeks. Executives speak, analysts probe, and the words - unscripted, spoken, fleeting - move markets. The bottleneck was never a lack of data. It was access: nobody could listen to all of it at once, quickly enough, accurately enough to act.
Aiera is a New York-based generative-AI platform built to close that gap. It sources, verifies, transcribes and summarizes corporate and investor events - earnings calls, investor days, shareholder meetings, industry conferences and macroeconomic announcements - and delivers them as live audio, real-time transcripts, sentiment scores and searchable summaries.
The platform covers more than 50,000 events a year across 15,000-plus global equities. Transcripts combine AI automation with human review to reach roughly 99.9% accuracy, typically finalized within one to three hours of an event ending, with real-time text streaming while the call is still live.
Access comes three ways: through Aiera's own desktop and mobile apps, through embeddable components dropped into a client's existing tools, and - increasingly the growth engine - through enterprise APIs and data feeds that pipe transcripts and event data straight into the systems analysts already use.
The through-line is provenance. In a regulated industry, an answer without a source is a liability. Aiera leans on transparent sourcing, full audit trails and centralized entitlements so that institutions can put generative AI to work without losing track of where a number came from.
Aiera launched in 2018 with a bold pitch: a "robo-analyst" that would issue AI-driven investment recommendations. Customers, it turned out, didn't want a machine's verdict. They wanted the raw signal - faster, and with a clear trail back to the source.
By 2019 the company dropped recommendations entirely and refocused on live investor-event access, real-time transcription and analytics. The abandoned idea cleared the way for the business Aiera actually is today.
Live, AI-generated transcripts of earnings calls and investor events with speaker diarization, timestamps and human review - ~99.9% accurate within 1-3 hours.
Enterprise APIs and data feeds delivering live and historical transcripts, event calendars and enrichment straight into analyst workflows and third-party platforms.
One-click live audio, keyword search, an event calendar and agentic research workflows across web and mobile.
Automated event summaries, topic extraction and sentiment analysis - including a conversational earnings-call assistant built with OpenAI.
Permissioned, auditable access to broker research, filings and news with model enrichment across Anthropic, OpenAI and Microsoft Azure.
Search and retrieve earnings calls, investor days and shareholder meetings with full transcripts, speaker ID and analysis in one environment.
Institutional investors, asset managers, hedge funds, investment banks and equity research firms. Named clients and partners span the Street:
The financial-AI field is crowded - AlphaSense, Hebbia, Fintool, Brightwave, Hudson Labs and others all promise to help analysts read faster. Most bet on search across documents that already exist: filings, published research, prior transcripts.
Aiera's bet is on the harder input - the live, spoken event. Hearing an earnings call as it happens, attributing the right words to the right speaker, and doing it across the whole market at once is a different engineering problem than searching a corpus after the fact.
Its second differentiator is neutrality. Aiera is deliberately model-agnostic, supporting Anthropic, OpenAI and Azure, and positions itself as infrastructure rather than a walled garden - the layer other tools plug into. In infrastructure, neutrality is leverage.
The third is trust by design. Transparent sourcing, entitlements and citation integrity aren't features bolted on for marketing; in regulated finance they are the price of adoption, and Aiera built around them.
B2B SaaS plus data licensing. Aiera sells subscription access to its apps and monetizes enterprise API and event data feeds, embeddable components and content-enrichment services to buy-side and sell-side institutions. Estimated annual revenue is approximately $8.9M.
Aiera occupies the "live events" corner of financial AI - the real-time transcription and event-intelligence layer that sits upstream of the summarizers and copilots. Less a chatbot, more the plumbing of equity research.
In June 2025, Aiera closed a $25M Series B. What made it notable wasn't the number - it was who wrote the checks. Ten of Wall Street's largest, and normally competing, research firms co-invested and joined the board, alongside expert network Third Bridge, with Microsoft as a strategic technology partner on Azure.
Aiera also stood up a Buy-Side Advisory Council of senior leaders from a dozen of the world's largest long-only and hedge-fund firms. Total funding to date is roughly $68 million.
Revenue is an external estimate (Apollo) and approximate. Bars are relative to total funding.
Ken Sena and Bryan Healey launch Aiera in New York to deliver AI-driven investment recommendations.
Aiera drops recommendations and refocuses on live investor-event access, real-time transcription and analytics.
Aiera scales transcript and event APIs, desktop/mobile apps and enterprise data feeds for institutional clients.
Adds AI summarization, sentiment analysis and a conversational earnings-call assistant built with OpenAI.
Ten major research firms join the board, Microsoft becomes a strategic partner, and Aiera formalizes its compliant-AI platform.
Former Head of Internet Research at Evercore and Wells Fargo; BA/BS from Wharton, University of Pennsylvania.
Previously led engineering on Amazon's Alexa voice assistant before turning speech AI toward finance.
"Together with our partners, we are building a secure and scalable AI ecosystem - one that enhances the value of research, safeguards intellectual property, and empowers more informed, real-time decision-making."
"By bringing together the world's top financial research institutions, we are ensuring AI innovation is developed responsibly within the highly regulated research domain."
Aiera's shift from robo-analyst to events platform is now taught in a Harvard Business School case: "A New Aiera for Equity Research."
CTO Bryan Healey brought voice tech built for Amazon's living-room assistant to the trading floor.
Ten normally-competing Wall Street firms co-invested in the same startup - a rare show of shared standards.
Ken Sena spent a decade rated among the top internet analysts before building the platform his peers now use.