Global technology leader achieves 75% cost savings and 88% faster document review with OpenText eDiscovery Aviator
A global technology company's legal team faced escalating eDiscovery costs, with document review consuming 75% or more of total eDiscovery expenses. Human reviewers required extensive training, supervision, and quality control, demanding significant time from senior attorneys and creating a bottleneck that prevented focus on strategic legal work.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Review memo submitted as prompt
The system required only the existing review memo—the same document already prepared for human reviewers—as its prompt.
Tools used
OpenText eDiscovery Aviator reviewlarge language model
Outcome
The AI-powered document review pilot achieved 75% cost savings and 88% faster completion time, compressing the review timeline from three months to a few days, while delivering classification quality that met or exceeded human-review benchmarks.
What failed first
Traditional document review workflows were inefficient, requiring extensive reviewer training, continuous supervision, and iterative quality control, with project timelines often spanning months.
Results
Time saved88%
Volume75% or more of its total eDiscovery expenses