Product update
3
min read

Confidence, reliability and validity at LEGALFLY

Written by
Dennis Montegnies
Published on
March 11, 2025

Legal AI should make work easier, not more complicated. However, mixed experiences with generic AI tools, such as ChatGPT, have caused some legal teams to delay adoption. When AI produces unreliable outputs or lacks transparency, in-house teams spend more time verifying results than the technology saves. Without trust in its outputs, AI becomes a liability rather than an asset.

LEGALFLY is designed for legal work. Its reliability is built on four pillars:

Anonymisation for data security 

Confidential information is automatically anonymised before processing, protecting sensitive legal data.

Source-backed responses for transparency

Every AI-generated insight is linked to a verifiable source, whether from internal documents or external legal frameworks.

Playbooks and structured redrafting for accuracy 

LEGALFLY doesn’t just suggest changes. It follows defined legal playbooks to ensure contract consistency and compliance.

Explainability and reasoning 

Users can see step-by-step how LEGALFLY arrived at its conclusions, improving trust in decision-making.

1. Anonymisation for data security

Every document processed by LEGALFLY is automatically anonymised before being analysed. You can choose from secure, single-tenant infrastructure or on-premise options. This remains true whether you work with LEGALFLY in platform or within the Microsoft suite.

Anonymisation extends beyond text to images, handwriting, and signatures. Handwritten text is translated into standardised fonts to prevent identification of the writer. Profile pictures and identifiable images are removed.

User data is never used to train AI models and is kept segregated with strict access controls. LEGALFLY is both SOC 2 Type II and ISO 27001 certified, meeting global standards for vendor security assurance.

2. Source-backed responses for transparency

AI-generated legal insights are only as reliable as their sources. LEGALFLY grounds its outputs in both internal documents and external legal frameworks, removing the risk of hallucinations. 

When you ask questions about a document, LEGALFLY identifies where in the text the answer is derived from. If external legal sources are relevant, LEGALFLY references them as well.
LEGALFLY also demarcates certain sites as unreliable sources, such as Wikipedia, so that they are never used to inform responses. 

3. Playbooks and personalised redrafting  

AI-driven contract review is useful, but automated redrafting can introduce errors if not properly guided. LEGALFLY addresses this by allowing you to define clear redraft instructions within playbooks. Instead of LEGALFLY generating a generic revision, legal teams can specify exact replacement clauses or structured guidelines.

For example, if a termination clause needs to follow a company’s standard wording, LEGALFLY will replace the identified issue with the pre-approved clause rather than an AI-generated alternative. This ensures consistency, reduces unnecessary modifications, and aligns contract revisions with company policies.

Additionally, LEGALFLY continuously improves its understanding of legal language by referencing an internal repository of company-specific precedents. Over time, the AI refines its redrafting based on past decisions, ensuring outputs are aligned with your company standards.

4. Understandable AI decisions

One of the biggest challenges with AI in legal work is the lack of transparency. Many AI tools provide outputs without explaining how they were generated. LEGALFLY takes a different approach by offering full reasoning transparency, so you can see exactly how it arrived at a specific redraft.

Rather than a black-box output, you can click a button to view the step-by-step logic behind AI-generated recommendations. This includes:

  • Referenced clauses – The specific parts of the document that informed the AI’s decision.
  • Playbook rules – Any predefined legal guidelines or company-specific policies applied.
  • External legal sources – If applicable, the external legal frameworks or case law used.

To make this transparency accessible beyond the person reviewing the document, LEGALFLY also allows you to download a full report on AI-driven decisions. This report can be shared with colleagues, so that legal reasoning is clear to everyone involved in the contract review or approval process.

See it in action

Arrange a call with a LEGALFLY specialist to test out the results for yourself.