Linkedin-in

Capabilities

Menu

Data Solutions

We engineer data architectures and pipelines to meet the real-time, multi-domain, and high-security requirements of defense, intelligence, and homeland missions. Our platforms are designed to integrate with existing C4ISR, GEOINT, and cyber systems while enhancing automation, traceability, and tactical data advantage through advanced AI/ML capabilities

Data Curation, Metadata Management, Tagging & Labeling
We operationalize data governance by automating metadata management and semantic enrichment at scale. Our technical capabilities include:

  • Schema Alignment and Metadata Harmonization using RDF, OWL, and DoW/IC-standard ontologies (e.g., UCORE, MAGE).
    NLP-based Entity and Relationship Extraction from multi-format inputs (e.g., ISR reports, SIGINT, FMV) using transformer-based LLMs tuned for domain-specific lexicons.
  • Auto-Tagging and Label Propagation across multi-tiered classification environments using BERT, CLIP, and custom vision/language models.
  • Full data provenance and lineage tracking to support auditing, reproducibility, and model retraining workflows.

We enable intelligent downstream workflows for targeting, pattern-of-life analysis, and situational awareness with curated, machine-interpretable data artifacts.

Intelligent Data Pipelines
Our pipelines are cloud-native , containerized, and infrastructure-agnostic—capable of operating across AWS GovCloud, C2S, SC2S, Azure Government, and disconnected/tactical edge environments. Features include:

  • Event-Driven Orchestration using Apache Airflow, Argo Workflows, and Kubernetes-native operators.
  • Stream Processing via Kafka, Pulsar, and Flink with low-latency SLAs to support real-time ISR exploitation and mission command.
  • Embedded ML Inference Pipelines using ONNX, TorchServe, or Triton for on-the-fly feature extraction, anomaly detection, and image segmentation.
  • Integration of data validation frameworks to enforce quality gates and schema conformance dynamically.

We support full lifecycle operations—data ingest, transform, feature engineering, and delivery—within multi-security enclave environments and JWICS/SIPR/NSANet topologies.

Secure Data-sharing and Data Fabric Architectures
Our data fabric solutions implement zero-trust architecture (ZTA) principles while enabling secure federation and discoverability across classified and compartmentalized networks. Core technical differentiators:

  • Policy-Based Access Control (PBAC) and attribute-based encryption (ABE) for fine-grained sharing of sensitive data artifacts.
  • A self-service approach with suite of tools designed to enhance cost efficiencies, process optimization and scalability featuring secure automated workflows, and ensuring robust governance and observability for data providers, consumers, and their data integrations
  • Cross-domain solution (CDS) integration for guard-enabled replication and controlled release across classification levels.
  • Automated Lineage, Audit, and Usage Monitoring using Apache Atlas, OpenLineage, and custom graph analytics pipelines.
  • Federated Query and Virtualization using Trino, DataHub, and Delta Sharing to allow analytics and ML across distributed, heterogenous data stores (e.g., S3, PostGIS, HDFS, Elastic).

We build architectures to support Joint All-Domain Command and Control (JADC2), Integrated ISR, GEOINT fusion, and cyber threat intelligence operations across the defense and homeland enterprise.

CASE STUDY: NGA Metadata Cataloging and Management Services (MCAMS)

NGA Metadata Cataloging and Management Services (MCAMS)

NGA provides critical support to the national decision-making process and the operational readiness of America’s military forces. Their mission is to provide timely, relevant, and accurate Geospatial Intelligence (GEOINT) in support of National Security objectives. To remain operationally effective within a fluid, unconventional domain, NGA must advance in capability and analytic methodology. Previous production systems lacked the tools to manage products and assets. NGA intelligence producers used a series of disconnected / unintegrated legacy systems in combination with collections of COTS products. Together, they are counterintuitive and insufficient in meeting mission needs and as a result, analysts were unable to discover and reuse assets to create new products.

OMNI provides software development and software engineering support to deliver the Apollo Metadata Management System (Apollo). Our software engineers, architects, and data engineers built the system on an unclassified development platform that can create, tag, and track metadata of legacy and new geospatial assets and products to enable discovery and reuse on all three domains. Through the Apollo user interface, an analyst or decision maker using the Apollo system can review and edit the metadata tags for work products and add comments and ratings to those products to facilitate collaboration, discovery, and reuse. This empowers users to efficiently provide and gather insights from data on an enterprise-wide basis. Apollo addresses the need to neutralize the challenges introduced by a complex data landscape, maximize the value of its assets, and empower data analysts to efficiently gather and share insights from those assets.