LegalEagle
05LegalBeta

LegalEagle

LegalEagle reads contracts like a specialist associate — extracting clauses, mapping risk, and assembling compliance checklists so counsel focuses on judgment, not search.

First-pass time
−55%
Clause coverage
98%
Missed risks
−40%

Demo

See it in motion

A short walkthrough of the agent loop — from signal in to decision out.

LegalEagle demo

Demo reel

MSA first-pass review

2:28

Overview

Case at a glance

Target users: In-house counsel, contract ops, and compliance teams.

01 — Problem

The friction

Contract review is slow, repetitive, and easy to miss critical clauses.

02 — Solution

The approach

A legal research agent that extracts clauses, ranks contractual risk against your playbook, and produces counsel-ready review memos.

03 — Value

Why it matters

Faster first-pass reviews with fewer missed obligations.

How it works

The agent loop

From raw signal to a decision LegalEagle can defend.

  1. 01

    Ingest

    Reads the contract, including scans, and segments it into sections and defined terms.

  2. 02

    Extract

    Builds a structured clause map — liability, termination, IP, data — before forming any opinion.

  3. 03

    Compare

    Measures each clause against playbook positions and past signed agreements.

  4. 04

    Report

    Ranks deviations by materiality and separates routine variances from what needs counsel.

Capabilities

What LegalEagle actually does

Built for In-house counsel, contract ops, and compliance teams.

  1. 01

    Clause extraction

    Pulls liability, termination, IP, and data terms into a structured map.

  2. 02

    Risk ranking

    Scores findings against playbook norms and preferred fallback positions.

  3. 03

    Compliance checklists

    Generates obligation trackers tied back to specific contract sections.

  4. 04

    Counsel memo

    Summarizes what needs human judgment versus routine redlines.

Architecture

How the system thinks

Data flows left to right: sources feed the orchestrator, specialists reason in parallel, tools execute, and one artifact comes out.

01

Sources

  • DataContract corpus
  • DataPlaybook rules
  • DataPrecedent library
02

Orchestration

  • OrchestratorLegal orchestrator
  • LLMReasoning LLM
03

Specialists

  • AgentExtraction agent
  • AgentRisk agent
04

Tools & output

  • ToolOCR
  • ToolVector search
  • OutputReview memo
  • Data
  • Orchestrator
  • LLM
  • Agent
  • Tool
  • Output

In action

A real exchange

An abbreviated conversation, close to what the agent actually returns.

LegalEagle
LegalEagle Session active
  1. You

    Review this MSA against our playbook.

  2. LegalEagle

    Eleven deviations, three of them material: uncapped liability in §9, a 90-day termination-for-convenience right favouring the counterparty, and IP assignment silent on background IP. The rest are wording variances within tolerance.

  3. You

    Draft fallback language for §9.

  4. LegalEagle

    Proposed a cap at twelve months of fees with your standard carve-outs, matching the last three agreements you signed. Flagged for counsel review — I do not send redlines.

Design decisions

Trade-offs worth naming

The constraints that shaped the system — and what was deliberately left out.

  1. 01

    Playbook is the source of truth

    Risk is measured against your written positions, not a generic notion of market standard.

  2. 02

    Extraction before judgment

    The clause map is built first and shown separately, so a reviewer can check the reading before trusting the risk score.

  3. 03

    Human sign-off enforced

    Nothing leaves the tool as a redline. Output is a memo for counsel, which keeps accountability where it belongs.

Honest limits

Where it stops, where it goes

What the agent does not handle today, and what comes next.

Current limitations

  • Scanned contracts depend on OCR quality.
  • Jurisdiction-specific nuance still requires counsel.
  • Not a substitute for legal advice.

On the roadmap

  • Obligation tracking after signature
  • Multi-language contract support
  • Learning from negotiation history

Stack

Technology

Nothing added without a concrete requirement behind it.

PythonLangGraphOpenAIpgvectorNuxt