Built AI
Built AI provides an AI-native operating system for institutional real estate that connects existing systems like Argus, Yardi, and Excel into a single knowledge graph. A deterministic calculation engine computes auditable financial metrics, while an embedded analyst generates IC memos and investor letters with full source traceability and human approval workflows.
- Property Technology
- Artificial Intelligence
- Data & Analytics
- Software Only
- AI Agents
- Financial Technology
Funding
Founders
Founder details are not available yet.
Product
Problem
Institutional real estate firms still rely on spreadsheets, email, and manual reconciliation across siloed systems like Argus, Yardi, MRI, and Excel. This fragmented workflow slows portfolio analysis, delays reporting cycles, and creates invisible risk from unreconciled data, costing analysts days of work for simple questions and limiting investor visibility.
Solution
Built AI provides an AI-native operating system that connects to existing systems of record and unstructured documents, normalizing them into a single knowledge graph of entities, documents, and cashflows. A deterministic calculation engine computes financial metrics like IRR, DSCR, and NOI with full auditability, while an embedded analyst authors IC memos, investor letters, and covenant packs in firm templates. Every output traces back to its source cell, page, or line, and all external actions require human approval before execution.
Target Audience
Primary customers are institutional real estate owner-operators, fund managers, and allocators including REITs, insurers, pensions, and sovereign vehicles that manage large portfolios and need continuous, auditable reporting across funds, assets, and counterparties.
Features
- Knowledge graph modeling of funds, assets, leases, tenants, loans, covenants, and counterparties as connected entities rather than files
- Deterministic calculation engine that runs IRR, DSCR, debt yields, cap rates, NOI bridges, and waterfall distributions as auditable math, not LLM arithmetic
- Connectors for Argus, Yardi, MRI, Excel, PDFs, and data rooms with no migration required
- Normalization layer that resolves differing terminology across documents into a common schema with source pointers
- Authoring engine that generates IC memos, investor letters, covenant packs, and lease abstracts in firm templates with traceable figures
- Human-in-the-loop approval workflow for all external actions, with zero autonomous sends
- Multi-tenant or single-tenant deployment options including BYO model and self-hosted configurations