Comparison · Sustainability

Vaia vs Hebbia

A best-in-class document-research grid, next to a platform that also runs portfolio and ESG work.

Last reviewed 3 September 2026

Vaia vs Hebbia: the short answer

Hebbia's Matrix is the strongest interface in the category for interrogating a large pile of documents: documents on rows, questions on columns, a sourced answer and reasoning chain in every cell.

Vaia is built for the work on either side of that: knowing what is in the portfolio before the questions are asked, and turning the answers into an IC memo, an LP report, or an ESG disclosure after.

Hebbia answers questions about documents. Vaia also runs the portfolio and the reporting the documents belong to.

What Vaia is

Vaia is an intelligence and operational layer for investment and sustainability work, built on two proprietary vertical LLMs: one trained for financial and investment reasoning, one for ESG, carbon, and regulatory frameworks. Each client runs in a dedicated single-tenant environment.

Five applications sit on one platform: Vaia GPT (IC memos, 25-page institutional due-diligence reports, and research from a firm's own documents); Olaf (an autonomous agent across screening, diligence, research, and memo creation); Prism (multi-framework ESG and carbon accounting across GRI, BRSR, TCFD, CSRD, SFDR, and GRESB on a 48,000+ emission-factor database); Family Office (entity-aware portfolio aggregation across public, private, and alternative assets with real-time valuations); and Wealth Advisory (a relationship-manager co-pilot with a client 360, suitability checks, and automated reporting).

Vaia deploys as an overlay on the systems a firm already runs, goes live in weeks, and comes with a dedicated delivery team that configures it and tunes models and templates through reporting cycles. Published benchmarks: FinBen 81.17% and VSIB 89.68% operational accuracy. Security documentation is at trust.vaia.co.in.

What Hebbia is

Hebbia is an AI platform for knowledge work in regulated industries, founded in 2020 by George Sivulka and based in New York.

Its flagship product, Matrix, is a tabular grid that puts documents on rows and questions on columns and writes a sourced answer into every cell, with a visible reasoning chain and the exact source passage behind each one. It uses a technique the company calls iterative source decomposition to run sub-tasks across full documents rather than retrieved chunks.

Matrix integrates with SEC filings, earnings-call databases, Dropbox, Box, and SharePoint; its 2025 acquisition of FlashDocs added branded PowerPoint, Word, and Excel generation. Hebbia has raised roughly $161M, reached a $700M valuation at its 2024 Series B, and reports customers including BlackRock, KKR, Carlyle, MetLife, Centerview Partners, and Oak Hill Advisors.

What Vaia adds alongside Hebbia

A holdings ledger: entity-aware portfolio aggregation across public, private, and alternative assets with real-time valuations and multi-currency consolidation.
Prism for ESG and carbon accounting: GRI, BRSR, TCFD, CSRD, SFDR, and GRESB mapping, Scope 1–3 on a 48,000+ emission-factor database, hotspot analysis, and net-zero pathway modelling, which is accounting rather than data-point extraction.
Investment thesis fine-tuned into the model, so deals are scored consistently regardless of who ran them.
A wealth-advisory module: RM co-pilot, client 360, and suitability checks.
A dedicated single-tenant environment per client, and a pilot on your own documents before procurement.

Feature comparison

	Vaia	Hebbia
Primary interface	Purpose-built applications per workflow, plus chat and agent	Matrix, a tabular document grid
Core model	Two proprietary vertical LLMs, fine-tuned per client	Proprietary agent framework orchestrating third-party frontier models
Primary buyers	Family offices, wealth firms, PE/VC funds, enterprise sustainability teams	Asset managers, PE and credit funds, banks, law firms
Document interrogation at scale	Agent-driven across firm data	Matrix grid, strong for very large document sets
Portfolio aggregation	Entity-aware across asset classes; real-time valuations; multi-currency	Not a platform capability
ESG and carbon	Prism: GRI, BRSR, TCFD, CSRD, SFDR, GRESB; Scope 1–3 on 48,000+ factors; net-zero modelling	ESG data extraction from documents; no accounting engine or framework mapping
Investment thesis	Fine-tuned into the model, consistent scoring across deals	Encoded per grid, in column prompts
Deliverable generation	Text, PDF, tables, graphs, reports; API-first	Branded PowerPoint, Word, and Excel via FlashDocs
Wealth advisory	RM co-pilot, client 360, suitability checks	Not covered
Due diligence	25-page institutional DD reports across six dimensions including ESG	Document analysis and memo drafting within Matrix
Source attribution	Source-referenced outputs, every workflow step traceable	Cell-level reasoning chain and exact source passage
Deployment	Dedicated single-tenant environment per client, standard	Enterprise deployment

When to choose Vaia over Hebbia

Aggregation across public, private, and alternative assets is part of the job, not an adjacent system.
ESG, carbon, or regulatory reporting sits alongside investment work and needs an accounting engine, not extraction.
You want consistent scoring across deals, with the thesis in the model rather than a column header.
Wealth advisory is part of the business.
You want to pilot on your own documents before entering a procurement process.

Consider both. A large asset manager might give a research function Matrix and give an allocator or sustainability function Vaia as a system of record.

Frequently asked questions

What are the main alternatives to Hebbia?

Hebbia is most often evaluated against AlphaSense, Rogo, Glean, Harvey, and Blueflame AI, and against research tools such as Daloopa and Affinity. Those are largely document-research and market-intelligence products. Vaia is the alternative when portfolio aggregation and ESG reporting sit in the same scope.

What is the difference between Vaia and Hebbia?

Hebbia's Matrix interrogates large document sets: documents on rows, questions on columns, a sourced answer in every cell. Vaia is built for the work on either side of that — knowing what is in the portfolio before the questions are asked, and turning the answers into an IC memo, LP report, or ESG disclosure after.

Is Vaia a good Hebbia alternative?

If the job is interrogating a very large pile of documents, Matrix is the strongest interface in the category. If aggregation across public, private, and alternative assets, or ESG and carbon accounting, is part of the same job, Vaia covers ground Hebbia does not.

Can a firm use both Vaia and Hebbia?

Yes. A large asset manager might give a research function Matrix and give an allocator or sustainability function Vaia as a system of record. They solve adjacent rather than identical problems.