Hebbia vs Sema4.ai (2026): which should you pick?

Pick Hebbia if

• Fits if you work in banking, private equity or credit and review big document sets
• Works for law firms pulling terms out of many contracts at once

Look elsewhere if

• Not for you if you want a published price, as only a demo request is offered
• Skip it if you are an individual or small team, since it is aimed at institutional finance and legal work
• Watch out: connectors such as FactSet or PitchBook depend on a licence you pay for separately
• Not for you if you want a free try, because none is offered

Pick Sema4.ai if

• Fits if you are an enterprise team that needs a record of what agents did
• Makes sense if you work on Snowflake and want agents there

Look elsewhere if

• Not for you if you want a price, as none could be read
• Skip it if you can't run a cluster, since self-hosting needs EKS or AKS and an identity provider
• Watch out: the docs say the API reference and SDKs are not yet written up for Version 3
• Not for you if you want a free plan, because none is on record

Hebbia

• No prices are published; the site only offers a demo request.
• It is built for institutional finance and legal work, not for individuals or small teams without those data sources.
• Many data connectors, such as FactSet or PitchBook, depend on the firm having its own license for that data.

Sema4.ai

• No pricing could be read: the vendor's site answered with a bot check, and the documentation states no prices.
• The docs say the API reference, the SDKs and deeper analytics surfaces are not yet written up for Version 3.
• Self-hosting needs your own cluster, such as AWS EKS or Azure AKS, plus an identity provider.

Hebbia

Max

An agent that takes on deal-team tasks such as modeling, screening a target list, spreading comps and recapping earnings calls from the firm's own data.

Matrix

A grid where rows are companies or documents and columns are questions, so one analysis runs across many sources at once.

Financial and filings data

Integrations listed include FactSet, S&P Global, PitchBook, Fitch Solutions, Octus and Moody's, alongside SEC filings and earnings transcripts.

Data room and file connections

Connectors are listed for Datasite, SharePoint, OneDrive, Box, Dropbox and Snowflake.

API access

The platform page shows firms building their own tools on Hebbia's API, including white-labeled front ends.

Security controls

The vendor says customer data is never used to train models, is siloed per customer, and can be processed regionally in the US or EU or on a dedicated tenant.

Sema4.ai

Projects with shared context

Projects hold files, instructions, data, memories, skills and integrations, and you can chat with a Project to build or change what is inside it.

Workflows and work items

Workflows run with triggers, including a bound email address, and produce work items with a drafted answer that people can confirm, correct or send back.

Connections and data sources

The docs list providers such as SharePoint, Microsoft Teams, Gmail, GitHub, Slack and Stripe, MCP servers, and Snowflake and Postgres data.

Audit and evidence record

Administration pages cover audit lenses, deterministic execution, isolation of runs and alignment with COSO controls.

Self-hosting

Deployment guides cover AWS EKS, Azure AKS and other targets, with identity providers such as Entra ID, Okta and Auth0 for sign-on.

Hebbia

Pricing could not be confirmed. See hebbia.com.

Sema4.ai

Pricing could not be confirmed. See sema4.ai.