SecurePro

Research & Innovation

SecurePro invests in forward-looking research to stay ahead of emerging threats and deliver next-generation capabilities to federal customers. Our R&D program spans AI, cybersecurity, autonomous systems, and advanced analytics — with direct application to live federal programs.

Featured Initiative

Active Research

Agentic AI Workflow for RMF & ATO

Transforming compliance into continuous, intelligent assurance.

Read the research brief

ATO timelines averaging 12–18 months create a persistent security gap in federal programs. SecurePro is developing an agentic AI system that replaces manual RMF workflows with autonomous, continuously-learning compliance agents — dramatically compressing ATO timelines while improving assurance quality.

  • Knowledge Base — digitized NIST controls, mappings, and RMF metadata for machine reasoning
  • Agent Orchestrator — specialized Policy, Evidence, and Authorization agents working in parallel
  • Reasoning Engine — LLMs combined with symbolic logic for auditable, explainable compliance decisions
  • Data Fabric — control-to-evidence relationship graph with full provenance tracking
  • Interface Layer — dashboards for security staff, Authorizing Official approvals, and audit exports
  • Forward: federated AI for cross-agency reciprocity, integration with Zero Trust metrics, continuous learning from every authorization
Agentic AIRMF / ATONIST 800-53LLMsSymbolic LogicZero TrustContinuous ATO

ARIA Labs — Applied Research & Innovation Accelerator

ARIA Labs is SecurePro's applied R&D engine for turning mission needs into evaluated, governed, and reusable technology accelerators — spanning applied AI, cybersecurity-aware prototyping, workflow automation, cloud-native mission platforms, and compliance-aware engineering. How it works: ARIA Labs moves from mission need to hypothesis, prototype, evaluation, security/governance review, pilot, and mission accelerator — so prototypes are assessed before being positioned for mission adoption.

Applied R&DActive ResearchConceptual / Illustrative Architecture

How ARIA Labs Works · Research-to-Mission Model

ARIA Labs research-to-mission model, seven stages: Mission Need, Research Hypothesis, Prototype, Evaluation, a mandatory Security and Governance Review gate, Pilot, and Mission Accelerator. This is an evaluated path, not a guaranteed delivery pipeline.
  1. 1

    Mission Need

    A concrete operational gap from a government or defense mission.

  2. 2

    Research Hypothesis

    A testable idea for how applied AI could close the gap.

  3. 3

    Prototype

    A working prototype built quickly to make the idea testable.

  4. 4

    Evaluation

    Rigorous, evidence-based measurement — powered by ARIA EvalForge.

  5. 5

    Security / Governance Review

    Mandatory Gate

    A mandatory security, compliance, and responsible-AI gate before any pilot.

  6. 6

    Pilot

    A controlled, real-world trial that validates value and safety in context.

  7. 7

    Mission Accelerator

    A tested, governable accelerator — for example, MissionHR Navigator.

Illustrative research-to-mission model. Represents an evaluated path — not a guaranteed delivery pipeline; not every research effort becomes a fielded capability.

Artificial Intelligence & Machine Learning

AI Research

SecurePro's AI research focuses on developing and operationalizing AI/ML systems that meet the unique reliability, explainability, and security requirements of federal mission environments. Our work spans supervised and unsupervised learning, large language model (LLM) adaptation, and production MLOps pipelines for classified and unclassified programs.

Technologies & Tools

PythonTensorFlowPyTorchMLflowKubeflowAWS SageMakerAzure ML
ARIA Labs

ARIA EvalForge

Prototype

LLM benchmarking and mission-fit evaluation — compares candidate models on quality, latency, cost, safety, reliability, and mission fit through repeatable, rubric-based workflows with human review.

Read the research brief
ARIA Labs

MissionHR Navigator

Concept

Source-grounded HR policy assistance for federal missions — retrieves from approved sources, cites them, and keeps a mandatory human-in-the-loop review gate before any action.

Read the research brief

AI-Enabled Threat Detection

Active

Applying supervised and unsupervised ML models to identify adversarial behavior patterns in large-scale network telemetry — reducing mean time to detect (MTTD) by up to 60% in pilot deployments.

LLM Adaptation for Federal Data

Active

Fine-tuning and deploying open-weight large language models on government-controlled infrastructure to enable secure, air-gapped NLP capabilities without dependence on commercial APIs.

Explainable AI (XAI) for High-Stakes Decisions

Research

Developing XAI frameworks that make ML model outputs auditable and interpretable for federal decision-makers — meeting emerging OMB AI governance requirements.

Cybersecurity & Cryptographic Innovation

Cyber Research

Our cybersecurity research program addresses the evolving federal threat landscape — from post-quantum cryptographic migration to autonomous threat response and zero-trust policy orchestration. We collaborate with national labs, CISA, and academic partners to mature next-generation defensive capabilities.

Technologies & Tools

CRYSTALS-KyberCRYSTALS-DilithiumOpenSSLNIST PQCPythonSuricataZeek

Post-Quantum Cryptography Migration

Active

Evaluating and implementing NIST-standardized post-quantum algorithms (CRYSTALS-Kyber, CRYSTALS-Dilithium) for federal PKI infrastructure migration planning.

Autonomous Zero Trust Orchestration

Prototype

Policy decision engine prototypes that dynamically adapt micro-perimeter rules based on real-time device health scores, user behavior baselines, and threat intelligence feeds.

Adversarial ML Defense

Research

Developing detection and mitigation techniques for adversarial attacks against AI/ML systems deployed in federal environments, including data poisoning and model inversion attacks.

Unmanned & Edge Intelligence

Autonomous Systems

SecurePro's autonomous systems research addresses the security and intelligence requirements for unmanned platforms, tactical edge computing, and DIL (disconnected, intermittent, limited) network environments. Our frameworks enable mission-capable autonomous operations without reliance on centralized infrastructure.

Technologies & Tools

ROS 2MAVSDKTensorFlow LiteOpenCVRusteBPFMQTT
ARIA Labs

MissionHR Navigator

Concept

Source-grounded HR policy assistance for federal missions — retrieves from approved sources, cites them, and keeps a mandatory human-in-the-loop review gate before any action.

Read the research brief

Secure Edge Computing Frameworks

Active

Architecting lightweight security control frameworks for tactical edge devices in DIL environments — enabling mission continuity without centralized infrastructure.

Autonomous Mission Planning AI

Research

Applying reinforcement learning and constraint satisfaction models to autonomous mission planning problems where real-time human oversight is limited.

Resilient Mesh Communications Security

Prototype

Security protocols for military mesh networking environments, including key management, authentication, and anomaly detection in bandwidth-constrained tactical networks.

Decision Intelligence & Data Science

Advanced Analytics

Our advanced analytics research focuses on transforming large-scale federal datasets into operationally relevant intelligence. We develop novel approaches to geospatial analytics, time-series forecasting, and multi-source data fusion — enabling faster, more confident decision-making across defense and civilian programs.

Technologies & Tools

Apache SparkDatabricksGeoPandasPostGISProphetRAPIDSTableau
ARIA Labs

ARIA EvalForge

Prototype

LLM benchmarking and mission-fit evaluation — compares candidate models on quality, latency, cost, safety, reliability, and mission fit through repeatable, rubric-based workflows with human review.

Read the research brief
ARIA Labs

MissionHR Navigator

Concept

Source-grounded HR policy assistance for federal missions — retrieves from approved sources, cites them, and keeps a mandatory human-in-the-loop review gate before any action.

Read the research brief

Multi-Source Data Fusion

Active

Developing probabilistic fusion models that integrate structured and unstructured data from heterogeneous sources — improving intelligence completeness and reducing false positive rates.

Predictive Analytics for Logistics

Active

Applying time-series forecasting and causal inference to defense logistics datasets, enabling predictive maintenance, supply chain optimization, and readiness forecasting.

Geospatial Intelligence Automation

Research

Computer vision and NLP pipelines that automate extraction and analysis of geospatial intelligence from satellite imagery and open-source reporting streams.

Explore ARIA Labs

Learn how SecurePro's applied research lab turns mission needs into evaluated prototypes, governed accelerators, and reusable solution patterns.

Demo the Capability

Interactive demonstration of SecurePro's retrieval-augmented AI capability — designed to support explainable, grounded answers over approved knowledge sources for federal mission and compliance workflows.

  • Grounds responses in authoritative source documents
  • Designed for RMF, ATO, and compliance use cases
  • Representative prototype for federal mission AI
  • Non-CUI environment — demonstration only

Powered by NVIDIA RAG Blueprint on dedicated AWS infrastructure. Demo availability depends on scheduled uptime windows.

SecurePro RAG Capability

Grounded AI responses over mission-relevant knowledge sources

Checking availability…

Representative prototype for federal mission and compliance workflows. Responses are generated from approved knowledge sources. Not a certified production system — for demonstration purposes only.

Selected Publications

Representative publications from the SecurePro research team. Contact us for full publication list and white papers.

Applying ML Anomaly Detection to Federal Network Monitoring: A Pilot Study

Thornton, M., Nair, P., et al.

DoD Cybersecurity Conference Proceedings · 2025

Migration Pathways to Post-Quantum PKI in Federal Environments

Whitfield, J., Chen, L.

IEEE Security & Privacy · 2024

Zero Trust Maturity in Practice: Lessons from Agency Deployments

SecurePro Research Team

CISA Zero Trust Summit White Paper · 2024

Edge Security for Tactical IoT: Constraints and Countermeasures

Nair, P., Rodriguez, A.

USENIX Security Symposium · 2023

Explainable AI in High-Stakes Federal Decision Systems: A Framework

SecurePro AI Research Team

AAAI Workshop on AI for Government · 2023

Innovation Initiatives

SecurePro participates in government-sponsored research programs and academic collaboration networks.

SBIR / STTR Programs

Active participation in Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) programs — developing prototypes for DoD and civilian agency sponsors.

University Research Partnerships

Collaborative R&D agreements with 4 national universities covering AI safety, post-quantum cryptography, and autonomous systems security.

National Lab Collaboration

Technical partnerships with national laboratory programs on advanced computing, cryptographic research, and edge intelligence frameworks.

CISA Joint Research

Participation in CISA-sponsored research initiatives on zero-trust maturity, critical infrastructure protection, and federal cybersecurity posture assessment.

AI Safety & Governance

Contributing to federal AI governance frameworks in alignment with OMB M-24-10 and NIST AI RMF — ensuring SecurePro's AI capabilities meet emerging federal standards.

Open Source Contributions

Active contributors to CNCF, OpenSSF, and DoD Platform One open-source projects — improving security tooling available to the broader federal community.

Interested in research collaboration?

We partner with universities, national labs, and government agencies on joint R&D initiatives. Reach out to learn about current collaboration opportunities.

Contact Our Research Team