Legal & Compliance AI

Where Open Active Comes In - Experienced Project Management

Project managers (PMs) are vital in orchestrating the development and enhancement of Legal & Compliance AI systems.

We handle strategic oversight, team coordination, and quality assurance, with a strong focus on training and onboarding workers to curate the data that powers these precision-driven systems.

Training and Onboarding

PMs design and implement training programs to ensure workers understand legal terminology, compliance standards, and annotation objectives. For example, in contract review, PMs might train workers to spot ambiguous clauses, using sample documents and legal guides. Onboarding includes hands-on tasks like tagging regulations, feedback sessions, and calibration exercises to align worker outputs with AI needs. PMs also establish workflows, such as escalated reviews for complex IP cases.

Task Management and Quality Control

Beyond onboarding, PMs define task scopes (e.g., annotating 5,000 contracts) and set metrics like accuracy, consistency, or clause detection rates. They monitor progress via dashboards, address inefficiencies, and refine guidelines based on worker feedback or evolving legal requirements.

Collaboration with AI Teams

PMs connect data curators with machine learning engineers, translating technical requirements (e.g., precision in compliance flags) into actionable tasks. They also manage timelines to ensure data delivery aligns with AI deployment cycles.

We Manage the Tasks Performed by Workers

The annotators, taggers, or legal analysts perform the detailed work of preparing high-quality datasets for legal and compliance applications. Their efforts are meticulous and context-sensitive, requiring legal literacy and precision.

Common tasks include:

Labeling and Tagging

For legal research, we might tag a case with “precedent” or “statute.” In IP labeling, they mark content as “copyrighted” or “public domain.”

Contextual Analysis

For contract review, our team analyzes terms, tagging “termination clause” or “penalty.” In compliance training, they assess logs, tagging “GDPR violation” or “compliant.”

Flagging Violations

In document annotation, our employees and subcontractors flag vague language (e.g., undefined terms), ensuring clarity. In compliance data, they mark non-compliant entries.

Edge Case Resolution

We handle complex cases—like ambiguous regulations or disputed IP claims—often requiring discussion or escalation to legal experts.

We can quickly adapt to and operate within our clients’ annotation platforms, such as proprietary legal tools or industry-standard systems, efficiently processing batches of data ranging from dozens to thousands of items per shift, depending on task complexity.

Data Volumes Needed to Improve AI

The volume of curated data required to train and refine Legal & Compliance AI systems is significant, driven by the complexity of legal language and regulations. While specifics vary by task and model, general benchmarks include:

Baseline Training

A functional model might require 5,000–20,000 labeled samples per category (e.g., 20,000 annotated contracts). For tasks like regulatory compliance, this could rise to 50,000 to cover diverse rules.

Iterative Refinement

To improve accuracy (e.g., from 85% to 95%), an additional 3,000–10,000 samples per issue (e.g., missed clauses) are often needed. For example, refining IP detection might demand 5,000 new documents.

Scale for Robustness

Large-scale systems (e.g., multinational compliance) require datasets in the hundreds of thousands to handle edge cases, jurisdictions, or rare terms. A legal research model might start with 100,000 documents, expanding by 25,000 annually.

Active Learning

Advanced systems use active learning, where AI flags uncertain data for review. This reduces volume but requires ongoing curation—perhaps 500–2,000 samples weekly—to maintain performance.

The scale demands distributed teams, often hundreds or thousands of workers globally, coordinated by PMs to ensure consistency and accuracy.

Multilingual & Multicultural Legal & Compliance AI

We can assist you with your legal and compliance AI needs across diverse linguistic and cultural contexts.

Our team is equipped to curate and process data for global legal applications, ensuring accurate and jurisdictionally relevant datasets tailored to your objectives.

We work in the following languages: