Apers vs. Hebbia

Overview

Hebbia is an AI-powered document intelligence platform used by financial institutions, law firms, and consulting firms for research and analysis across large document libraries. It excels at searching, synthesizing, and answering questions across hundreds or thousands of documents simultaneously. Think of it as an AI research analyst that can read your entire document repository and answer complex questions about it.

Apers is a CRE-specific underwriting system that reads deal documents, extracts structured data, and generates financial models. It's focused on going from a specific deal's documents to a specific deal's Excel model.

The distinction is between document research (Hebbia) and deal underwriting (Apers). Both involve reading documents and producing analysis. The type of analysis — and the output format — is fundamentally different.

Feature Comparison

Table 1 — Hebbia is a document research platform. Apers is a deal underwriting system. Both read documents, but for different purposes and with different outputs.

Research vs. Underwriting

The clearest way to understand the difference:

Hebbia answers questions like:

• "What are the lease expiration dates across all 15 properties in this portfolio?"
• "How do the environmental provisions compare across our last 20 purchase agreements?"
• "Which properties in our portfolio have change-of-control clauses in their ground leases?"
• "Summarize the key risk factors mentioned across all OMs we've reviewed this quarter."

Apers answers questions like:

• "Build an acquisition model for this multifamily deal with a 70/30 promote above 12% IRR."
• "Extract the rent roll from this OM and generate a cash flow projection with a 3% rent growth assumption."
• "Size the senior debt at 65% LTV with a 1.25x DSCR minimum and add a mezzanine tranche."
• "Model this as a 4% LIHTC deal with tax-exempt bonds."

Hebbia helps you research and synthesize. Apers helps you model and underwrite. One is about understanding what's in your documents. The other is about turning documents into investment decisions.

When Hebbia Wins

• Portfolio due diligence. Reviewing 15 OMs for a portfolio acquisition and comparing key terms, risk factors, and assumptions across all properties simultaneously. Hebbia's multi-document search is built for this.
• Legal document review. Comparing lease clauses, partnership agreement terms, or loan covenants across a library of documents. Hebbia can find patterns that manual review would miss.
• Market research. Synthesizing information from market reports, broker research, and industry publications to inform investment strategy.
• Institutional knowledge. "What did we underwrite for exit cap rate on our last five Phoenix multifamily deals?" If the answer lives in past documents, Hebbia can find it. (For Apers' approach to institutional knowledge, see the knowledge engine.)

When Apers Wins

• Deal-specific underwriting. Going from "here are the deal documents" to "here's the IC-ready model" — the core workflow Apers was built for.
• Financial model generation. Hebbia can tell you what's in a document. Apers builds the Excel model that uses that information to calculate returns, size debt, and model distributions.
• Structured extraction to model. Pulling the rent roll, T-12, and property details out of documents via Apers' document intelligence engine and mapping them directly to financial model assumptions with cell-level citations.
• Complex modeling. Waterfall distributions, LIHTC basis calculations, development pro formas, multi-tranche debt sizing. These are computational tasks, not research tasks.

Using Both

For institutional teams with both research and underwriting needs, Hebbia and Apers serve different phases:

1. Hebbia (research phase): Review the OM library. Compare the new deal's terms against past deals. Identify risk factors and market patterns. Answer research questions that inform your investment thesis.
2. Apers (underwriting phase): Take the deal documents, generate the financial model, size the debt, model the waterfall, run sensitivity analysis. Produce the IC-ready output.

The research informs the underwriting. The underwriting produces the decision. Different tools for different cognitive tasks. For a broader view, see our full comparison overview.