What for: privacy-first AI for legal teams with built-in data anonymization — contract review, drafting and due diligence.

What it is and who it's for

LEGALFLY is AI for legal teams with a strong privacy focus: sensitive data is anonymized before processing, on top of review, drafting and due diligence. It's for in-house teams and firms (especially in Europe) where data protection and control over what reaches the model are critical. What sets it apart is that anonymization/de-identification is the core of the product, not an add-on.

Key features

Data anonymization/de-identification before any AI processing.
Document review and drafting, due diligence.
Risk checks and playbook compliance.
Working with the organization's knowledge base and documents.
Security and compliance focus (privacy-first).
Integrations into legal workflows.

Get started in 5 minutes

Request access or a demo at legalfly.com (it's a team product).
Configure the anonymization rules and upload documents into the secure workspace.
Run review, drafting and analysis — data is processed with de-identification applied.

When to use it, and when not to

✅ Use it if: data privacy is priority number one and you need anonymization before AI processing.
✅ Use it if: you're a European team with data protection requirements.
❌ Skip it → go with "Harvey" if you need the broadest enterprise platform and adoption in large firms.
❌ Skip it → go with "Spellbook" if contract review inside Word is enough and anonymization isn't a focus.

The honest price

Paid team subscription (through demo/sales), priced individually. Exact figures are with the provider and change over time.

Gotchas

Anonymization lowers the risk but doesn't replace reviewing the provider contract and where data is processed.
The product is younger than the big names — assess its maturity and support for the languages and law you need.
AI output still needs a lawyer's review.
Check applicability to Russian law on your own documents.

🤖 Prompt accelerator

"I'm considering LEGALFLY for legal data privacy. Help me draft pilot requirements: how the anonymization actually works (what gets de-identified, where data is processed), GDPR and internal policy compliance, support for the jurisdictions and languages we need, and review/drafting quality on our documents . Give me a security checklist for the evaluation."