Super is a primary example of a vertical agent application that moves beyond single-task automation. Their system utilizes a multi-agent orchestration framework where a central 'coordinator' agent determines intent and delegates tasks to specialized sub-agents (Maintenance, Leasing, Reception). This architecture is particularly relevant to the agent ecosystem as it demonstrates how multi-agent systems can handle complex, real-world workflows in regulated environments.
They are active in the 'Application' and 'Vertical Agent' layers of the stack, specifically pushing forward autonomous voice interactions. By owning their voice pipeline and integrating deeply with industry-specific databases, Super provides a blueprint for how agents can move from 'chatbots' to 'action-oriented workers' that can independently log work orders and schedule appointments in external systems of record.
Super builds voice infrastructure specifically for property management, a sector where missed calls represent lost leasing revenue and unresolved maintenance liabilities. Founded in 2021 by Lindsay Liu (ex-Meta) and Vika Kovalchuk Zamparelli (ex-Google), the company was born from the founders' own frustrations as property owners dealing with unresponsive management teams. Unlike the wave of startups built as thin wrappers over OpenAI's GPT-4o or generic voice APIs, Super operates its own custom voice pipeline. This technical choice allows them to manage sub-second latency targets and deploy specific features like background noise suppression and sophisticated voicemail detection that are necessary for professional real estate operations.
At the core of the platform is an intent determination layer that acts as a switchboard. When a resident or prospect calls the main line, the system does not just follow a rigid phone tree. It uses an orchestration framework to decide which specialized agent to deploy. A call about a leaky faucet triggers a maintenance agent that knows how to create work orders, while a call about a vacant apartment activates a leasing agent capable of property matching and scheduling showings. This multi-agent approach allows the system to resolve approximately 34% of inquiries without human intervention, a significant shift for an industry that typically misses up to 60% of its calls.
Data in property management is notoriously fragmented across various Property Management Systems (PMS). Super maintains two-way integrations with these systems of record to provide its agents with real-time context. This 'Property Brain' allows the AI to know if a resident has a past-due balance before they ask for a repair, or to pull the exact square footage of a unit for a prospective tenant. By translating technical PMS data into natural conversation—such as turning a unit code like 'P2-10-MS' into '10 Main Street'—the agents maintain a higher level of perceived utility than general-purpose assistants.
Real estate is a highly regulated field, and Super emphasizes compliance as a core product principle. Their agents are pre-trained on Fair Housing Law and industry-specific terminology. This specialization is designed to prevent the 'hallucination' risks often associated with general LLMs, ensuring that an automated response doesn't inadvertently violate federal housing regulations. The company operates on a usage-based pricing model, starting at around $150 per month for outreach and scaling up based on the complexity of the orchestration and call volume. This makes the technology accessible to both small single-family rental portfolios and large multifamily asset managers.
A 24/7 front desk voice agent that handles inbound calls, texts, and emails for property management teams.