Ken Sena runs a company that listens to Wall Street so people do not have to. From an office on Park Avenue, his firm Aiera - pronounced like "era" - captures earnings calls, investor presentations, and corporate events as they happen and turns them into searchable transcripts, sentiment threads, and machine-readable summaries. Today the platform covers more than 13,000 equities and processes upward of 45,000 public events a year. For a decade before any of that, Sena was the one sitting on those calls himself.
As CEO and co-founder, Sena is building for a version of himself that no longer exists: the analyst pulling apart a quarterly call at midnight, hunting for the sentence that moves a stock. That lived experience is the spine of Aiera. He is not an outsider guessing at a workflow. He spent roughly two decades inside it, which is why the company's pitch has always been less about spectacle and more about the unglamorous mechanics of research getting faster.
The near-term work is deliberate. In June 2025 Aiera closed a $25 million Series B, and the backing was as notable as the number: ten of Wall Street's largest research firms joined, alongside the global expert-network firm Third Bridge. Microsoft came on as strategic technology partner, providing the Azure infrastructure behind Aiera's generative AI. The money is aimed at sharpening language-model accuracy, hardening intellectual-property protections, and giving customers a platform they can embed generative AI into directly.
A desk with a view of the whole internet
Sena's route into finance ran through research from the start. He began at Salomon Smith Barney, then moved through the industry during the years the web was rewriting what a public company could be. He worked at Bear Stearns and Credit Suisse, and took strategy and business-development turns at media giants Viacom and Time Warner, seeing the other side of the analyst's coverage universe from inside the companies themselves.
His most visible chapter came at Evercore ISI, where he served as senior managing director and global head of internet research coverage. In that seat he was paid to have an opinion on the companies reshaping daily life, and to defend it in front of institutional investors who did not accept conclusions on faith. It is a job that rewards pattern recognition and punishes hand-waving, and it left him with a precise sense of where research time actually goes.
In 2017 he moved to Wells Fargo Securities to run internet research there. It was inside the bank that the seed of Aiera was planted, in the form of an internal project exploring how machine learning might carry some of the load. About a year later he left to build it as an independent company. Aiera launched its platform in 2018, early enough that being early was itself the hard part.
The skeptics in the room
When Aiera opened its doors, the mood around AI in finance was cautious. Institutional investors, trained to distrust anything they could not audit, were reluctant to treat a model as a source of truth. Sena has been candid that he underestimated how steep that climb would be. "It was early in AI," he has said, "and institutional investors were skeptical of it as a source of truth, much more than they are today."
That skepticism shaped the product philosophy. Rather than promising to replace analysts, Aiera positioned its technology as an amplifier for them - a way to hear more calls, catch more numbers, and surface sentiment shifts without adding headcount. Sena has framed it plainly: Aiera "is not about replacing decision making with automation; it's about improving the workflow and making its users more efficient." His co-founder and CTO, Bryan Healey, has put the same idea in sharper terms, describing a belief in "the marriage between human and AI as an efficiency tool and performance enhancer, and not in using AI as a straight replacement."
The distinction is not marketing gloss. In a field where "AI replaces X" is the default headline, choosing to sell augmentation to a suspicious buyer is a slower, harder path. It asks the customer to keep their judgment and hand over only the grunt work. For a former analyst, it also happens to be the honest description of what the tool does.
What the machine actually does
Strip away the framing and Aiera is a system for turning talk into data. Earnings calls, conference appearances, and investor days are sourced, verified, and transcribed in real time. Speech becomes text; text becomes topics, sentiment, and summaries; and all of it becomes searchable across a coverage universe far larger than any single analyst could track by hand. The company also runs live event streaming and API data feeds, so the output can flow straight into a firm's own tools.
The scale is the point. A human analyst might cover a few dozen names well. Aiera's stated coverage of more than 13,000 equities and tens of thousands of events a year is a different order of magnitude, and it is only useful if the transcription is accurate and the insight is trustworthy - which is exactly where the Series B money is aimed. Improving language-model accuracy and protecting clients' intellectual property are not side quests here; they are the conditions under which a skeptical industry agrees to rely on the system at all.
A case study, and a council
The clearest sign that Aiera moved from curiosity to case study is that it literally became one. In early 2024, Harvard Business School published "A New Aiera for Equity Research," using the company to teach a harder question than any single feature: how do you get an entrenched industry to change the way it works? The interesting part of Sena's story is not that he built a transcription engine. It is that he had to persuade the buy side and the sell side to trust it.
He has built the persuasion into the company. Alongside the Series B, Aiera formed a Buy-Side Advisory Council to steer product development through direct feedback from the investors who use it. It is a founder's move that fits him - the same instinct that made him a credible analyst, now pointed at making a credible product. Listen to the people whose money is on the line, then build for what they actually need.
The composition of the 2025 round carries its own message. When ten of the largest research firms on Wall Street put money into a company that reads and structures the same events they cover, they are not betting against their own analysts. They are betting that the reading gets commoditized and the judgment does not. Third Bridge, a global expert-network firm, joining the round points the same direction: the value migrates toward interpretation, and the raw capture becomes infrastructure. That is a comfortable thesis for a founder who has always argued the analyst is the point and the transcription is the plumbing.
Naming an era
There is a small tell in the company's name. Aiera reads as "AI" fused into "era," and it is meant to be said like the word - a bet, planted in the branding, that a new period in financial research was arriving whether or not the market was ready. When Sena chose it in 2018, that was closer to a wager than a fact. The 2025 round, with Wall Street's biggest research names on the cap table, reads like the wager paying off.
Sena's education sits behind all of it: a dual degree from the Wharton School and Penn's College of Arts & Sciences, the kind of finance-plus-liberal-arts grounding that shows up in someone who can both model a business and explain why it matters. What comes through in his public comments is patience more than flash. He spent years defending research calls, years watching AI mature from novelty to necessity, and years convincing a cautious industry one firm at a time.
The aspiration he describes is consistent with the pitch he has made from the beginning: a secure, scalable AI ecosystem for financial research that makes analysts and investors faster and better informed, keeps their intellectual property safe, and keeps human judgment at the center of the decision. For someone who once did the listening himself, building the thing that listens at scale is less a pivot than a continuation - the same job, handed to a machine he trusts because he knows exactly what it is replacing and what it is not.