Prometheus.ai.

The problem

Independent landlords run rental portfolios through disconnected spreadsheets, manual inspections, reactive maintenance, and jurisdiction-by-jurisdiction rent compliance lookups — what the product calls the industry's operational debt. The Portfolio Landlord spends 12-20 hours a week operating across four to six separate tools.

Rent-increase compliance research is the most frequent and severe pain: landlords manually cross-reference RGB guidelines, DHCR records, and lease terms across government portals, where errors carry legal and financial consequence. Contractor coordination runs over text and phone with no job visibility, market timing lacks unit-level comp data, and when an increase is disputed, landlords reconstruct a defensible audit trail by hand from emails, receipts, and spreadsheets under pressure.

The solution

Prometheus.ai is an orchestration engine for landlords and real estate investors that replaces spreadsheet-heavy workflows with AI agents spanning compliance, investor support, tenant communication, and renovation planning. The chosen focus is PrometheusAI, a conversational operating intelligence layer: rather than knowing which tab to open, the landlord asks "what should I do about Unit 3B this month?" and gets a synthesized, actionable brief.

Key differentiators include compliance-gated execution (Sentinel validates every rent action against jurisdiction-specific policy-as-code before execution, as a legal shield) and Vision AI for physical assets (Nemesis reduces a 4-hour manual inspection to a 4-minute forensic report). The Upgrade agent renders apartment upgrades from a photo and estimates cost and equity impact for investment decisions.

How it works

PrometheusAI runs on the Claude model family. Claude Opus 4.8 is the core conversational and reasoning layer, chosen for holding city, county, state, and federal rent rules simultaneously without collapsing to one jurisdiction, strict output structure, and resistance to fabricating regulatory citations. Claude Vision powers Nemesis damage classification and multi-image before/after completion verification, and Claude Haiku 4.5 routes high-frequency, low-complexity tasks like prompt cards and rent-gap ranking at low cost.

Every call layers static system instructions, dynamic portfolio context injected as structured JSON, and the landlord's query, so figures are grounded rather than fabricated. The master prompt enforces a summary-first structure, requires flagging compliance risk in the first sentence, and mandates the four rent-increase elements — current rent, market rate, legal ceiling, recommended ask — in order. An AEGIS RAG layer grounds policy and lease queries in uploaded documents, and Sentinel remains the authoritative compliance source; the model is prohibited from citing training data for regulatory figures.

Who it's for

The customer base is B2B, sold to real estate operating entities. The primary and most revenue-generating persona is the Portfolio Landlord — an owner-operator with 5 to 30 (often NYC) units who self-manages with QuickBooks and spreadsheets. Other buyers include the Property Management Principal running a boutique firm of 80-200 units and the Real Estate Syndicator who needs acquisition and renovation-ROI analytics.

Secondary users are Compliance Officers using Sentinel's human-in-the-loop dashboard, field techs logging trips and receipts, and tenants using the Tenant Portal — revenue-neutral but churn-protective. The product serves a non-technical, time-scarce operator who can't afford a separate compliance attorney, forensic inspector, and acquisitions analyst but needs all those functions.

Why it matters

Global PropTech is growing at 16.8% CAGR toward $86B by 2032, with 22 million US landlords managing 48 million units and less than 3% using AI-native tooling. NYC's regulatory complexity — DHCR, RSA, Local Law 18, preferential rent — serves as a defensible moat, and the next 3-5 years are a land-grab window before AppFolio, Yardi, and Buildium bolt AI onto legacy platforms.

Revenue is tiered B2B SaaS subscription ($79 to custom pricing) plus performance fees, one-time report purchases, and anonymized data licensing. At pre-seed founder stage with all 11 agent modules built at demo quality, the product is being validated on the founder's own portfolio before an external beta. Compliance is treated as the top-priority failure class: regulatory hallucination targets zero untraceable citations, and success is measured by zero DHCR violations post-launch.

At a glance

Project

Prometheus.ai

Built by

Roger Hercules

One-liner

Prometheus.ai is positioned as an orchestration engine for landlords and real estate investors managing rental portfolios.