Leighton Asia

Leighton Asia, a major construction and infrastructure contractor operating across multiple Asian markets, faced mounting legal costs driven by complex, high-volume e-discovery demands. Large construction enterprises routinely generate extensive documentation — contracts, correspondence, engineering records, and project files — that must be reviewed and produced in litigation and regulatory matters. Traditional linear document review, relying heavily on outside counsel and managed review teams, was neither cost-efficient nor scalable. The per-document cost of manual review, combined with the volume typical of construction disputes, made e-discovery one of the most significant and difficult-to-control items in the legal department's budget.

Leighton Asia engaged Exigent, a global alternative legal services provider, to modernize its e-discovery operations using DISCO's cloud-native platform. DISCO's machine learning and predictive analytics capabilities — specifically its AI-assisted review and continuous active learning models — were deployed to prioritize and cull the document population before human reviewers engaged. Rather than replacing the review team, the technology ranked documents by relevance and privilege likelihood, concentrating attorney effort on high-value materials. Exigent managed the end-to-end workflow, integrating DISCO into Leighton Asia's matter management process and providing the project management layer that connected the platform's outputs to legal strategy. The cloud-native deployment avoided on-premises infrastructure requirements, enabling rapid onboarding.

The combined Exigent and DISCO engagement delivered a 40% reduction in e-discovery costs for Leighton Asia — a substantial improvement for a corporate legal department where outside counsel and review spend typically represent the largest variable cost line. The AI-assisted review model reduced the volume of documents requiring human review, compressing review cycles and enabling faster matter resolution. Qualitative outcomes included greater predictability in legal spend forecasting and reduced dependency on large outside counsel review teams for routine document-intensive matters.

• 40% reduction in total e-discovery costs
• Accelerated document review cycles through AI-driven prioritization
• Reduced reliance on high-cost linear review workflows

• Pairing a managed legal services provider with a modern AI-powered platform compounds cost savings: Exigent's project management expertise and DISCO's predictive analytics each amplified the other's value.
• Cloud-native e-discovery eliminates infrastructure barriers and enables faster deployment for regional legal teams operating across multiple Asian jurisdictions.
• Technology-assisted review (TAR) with continuous active learning consistently outperforms linear review on both cost and accuracy metrics at enterprise document volumes.
• Corporate legal departments in construction and infrastructure should treat e-discovery platform selection as a strategic cost-control lever, not a vendor commodity decision.