About
Practitioners in evidence-grade data work
NEXUS was built by engineers who have run document pipelines where every output may be challenged. That shapes how we work: local processing, complete records, and plain reporting of what was and was not achieved.
What we believe
AI belongs in sensitive workflows only when every step can be explained, repeated, and checked.
Your data stays under control
We process on hardware we operate or inside your environment, and use external AI providers only with your approval.
Originals are preserved
Redactions, translations, and enhancements are separate, labeled derivatives. Source files are never overwritten.
People approve irreversible steps
Production, redaction, and deletion wait for a named reviewer.
Results are reported honestly
We state what was tested, on what data, and where the limits are.
Tooling we build
We develop our own tooling rather than reselling a single platform, so we can adapt it to each matter.
- Forensic OCR platform. GPU and CPU OCR with language routing, crash recovery, and hash-chained custody logs.
- Translation service. Contract-based translation that keeps source text, provider details, and review notes together.
- Enrichment pipeline. A shared job and evidence framework for speech, vision, forensic, and governance enrichments.
- Document similarity engine. Dense, visual, and lexical similarity with near-duplicate grouping.
- eDiscovery tooling. RSMF conversion, an offline load-file workbench, and a review platform.
- News intelligence pipeline. Continuous ingestion, summaries, and bias and framing analysis across many sources.
Infrastructure
Owned GPU compute for private enrichment, fine-tuning, and inference.
Workloads run on NVIDIA DGX Spark (GB10) systems that we operate. Pipelines are packaged for Kubernetes, so they can also run on-premises or in a customer's own environment.
Have a data problem that will not fit in a spreadsheet?
Tell us what the data is, where it lives, and what it needs to answer. We will tell you plainly what we can deliver, how we would test it, and what it would take.