EliseAI Builds Operational AI for Essential Services

EliseAI is a New York artificial-intelligence company building operational software for housing and healthcare. Founded in 2017 by Minna Song, CEO, and Tony Stoyanov, CTO, the company started with leasing and resident communication, then expanded across the work that surrounds those conversations.

EliseAI now automates workflows spanning tours, maintenance, renewals, delinquency, scheduling, patient intake, prior authorizations, and front-desk communications. The company says it has passed $200M in annual recurring revenue, doubled revenue year over year for five consecutive years, reached one in five U.S. apartments, and supported 2M patients. Those are company-reported figures from a privately held business.

The company matters because vertical AI is moving from language to authority. The useful question is no longer whether software can answer a resident or patient. It is whether the system can carry the right context, permission, exception, and next action through a workflow without leaving a human to clean up the handoff.

About EliseAI

EliseAI began as MeetElise with a narrow but stubborn problem: property-management teams were trying to answer leasing questions across fragmented channels while preserving enough context to move a prospect forward. Song and Stoyanov were technical founders without traditional real-estate backgrounds, which forced them to learn the operation from customers rather than inherit its assumptions.

That apprenticeship became a product strategy. Song has written that the founders spent their first two years building, selling, and talking directly with customers before raising institutional capital. By then, the platform supported leasing across 100,000 apartments and had signed two of the country's largest owner-operators, according to Song's account.

The result is a company built around workflow depth. EliseAI's housing platform connects communications with leasing, tours, maintenance, renewals, delinquency, audits, and reporting. In healthcare, the same operating idea reaches scheduling, intake, prior authorizations, billing, prescription follow-up, and call-center work.

Why EliseAI Matters Right Now

Housing and healthcare are essential services with an almost comic amount of administrative friction, except the consequences are not funny. A lost housing handoff can mean a missed tour, an unresolved maintenance request, or a resident who has to explain the same issue again. A lost healthcare handoff can delay an appointment, a prior authorization, or access to the right staff member.

General-purpose AI can produce a fluent answer. EliseAI is trying to own what happens next. The company integrates with the systems its customers already use, keeps a history of the interaction, applies domain rules, and pushes work toward completion.

That operating depth helps explain why EliseAI expanded from housing into healthcare in 2023. Both markets are large, regulated, labor-intensive, and full of edge cases. They reward software that knows the workflow and punish software that merely sounds confident near it.

Apollo Turns Context Into Action

Apollo is EliseAI's clearest statement of where the platform is heading. The agent sits inside EliseCRM and related applications, inherits a user's permissions, and can take actions such as messaging prospects, updating knowledge, reassigning tasks and tours, changing settings, and generating dashboards.

EliseAI says Apollo has access to the platform's settings surface, uses a semantic layer over company data, and has been tested across more than 7,000 evaluations. Those details matter because an action-taking agent needs a different safety case from a chatbot. Permissions, data definitions, repeatable evaluation, and visible escalation are part of the product.

The strategic move is from conversation automation to an operating layer. A system that answers a leasing question saves time. A system that understands the prospect, books the tour, updates the record, and follows the business's rules changes how the work is organized.

Scale Raises the Proof Standard

EliseAI reported more than $200M in ARR in June 2026 and said revenue had doubled year over year for five consecutive years. Its September financing announcement placed the platform in one in five U.S. apartments. The official site also reports more than 1B AI conversations and 2M patients supported.

The company's customer stories name operators including WinnCompanies, The Michaels Organization, Landmark Properties, RPM Living, and Asset Living. These are company-curated case studies, not universal performance benchmarks, but they show that EliseAI has moved beyond a pilot-scale product in housing.

Scale also makes every weak edge visible. An error repeated across millions of conversations is not a rounding issue. EliseAI has to prove that its software can handle local policy, customer configuration, compliance, and unusual cases while preserving the operational consistency buyers want from automation.

Leadership Built Close to the Workflow

Song and Stoyanov's founding pattern is part of EliseAI's advantage. The pair stayed close to implementation before they had a large team to absorb the mess. That can produce a durable kind of knowledge: not simply what customers request, but which details determine whether the software survives a busy Monday morning.

The capital base is now very different. EliseAI announced a $250M Series E in August 2025 at a valuation above $2.2B. On September 29, 2026, it announced another $350M at a $4B valuation, led by Andreessen Horowitz, Bessemer Venture Partners, and Ontario Teachers' Pension Plan, with Sapphire Ventures and Navitas Capital participating.

That financing gives EliseAI room to expand the workflows its products can carry and to grow engineering, deployment, and sales teams. It also turns the company's culture of product speed into a larger management test. Startup urgency is useful. Reliable operational software still needs discipline after the headcount and customer base stop looking like a startup.

Hiring Is a Deployment Signal

EliseAI's careers page presents an in-office, high-ownership culture and lists openings across multiple functions. The important signal is not the benefits list. It is the mix of work required to make vertical AI useful: building the platform, integrating customer systems, deploying it into real operations, and supporting teams whose workflows do not pause for a model update.

Deployment belongs beside engineering in this category. Housing and healthcare customers carry legacy systems, local rules, uneven data, and institutional habits. A product can be technically impressive and still fail if it cannot map those realities into a reliable operating process.

That is the company-building challenge behind EliseAI's momentum. The business has moved from a focused communications tool into infrastructure that customers may allow to act. The next stage will be measured by how much work the platform can safely absorb, how clearly customers can govern it, and whether the automation remains worth trusting when the easy cases are gone.

EliseAI is not interesting because it put AI into two large industries. Plenty of companies can make that slide. It is interesting because it spent nearly a decade learning where the work actually breaks, then built toward the permission to carry more of it.