CAPABILITIES

Three deployment tiers. Same kernel. Same DAG.

Almighty deploys at three postures: synthetic exercise control, live-fire augmentation, and forward-deployed hardened edge. Each tier inherits the previous one. The kernel does not change across tiers — only the surface area, the integration footprint, and the deployment posture.

01Tier

Training

Exercise Control Tier

For exercise controllers running synthetic wargames inside a closed range LAN.

  • Synthetic blue / red / white cell crews
  • PyRapide DAG with per-(tenant, scenario) namespacing
  • Three override scopes — per-event, per-agent-per-turn, per-turn
  • AAR replay rebuilt from per-tenant Postgres
  • Resium 3D battlespace with capability-gated CZML templates
  • Unclassified banner on every visual surface
Who it's for

Brigade-level wargaming and EXCON cells running synthetic exercises against blue / red / white cell crews. Notional theater, multi-tenant range, full AAR replay. PyRapide kernel, Resium battlespace, override gateway.

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02Tier

Live Augmentation

Live-Fire Tier

For live-fire training where real device telemetry feeds the same DAG.

  • Everything in Training, plus —
  • DIS / HLA adapter contracts for live device telemetry
  • Sensor / Effector / Mover / Communicator / Commander tools
  • Capability-profile-validated officer interfaces
  • Per-tenant AWS isolation — VPC, RDS, S3, KMS
  • Continuous AAR with deterministic replay
Who it's for

Combined arms ranges where instrumented vehicles, dismounted radios, and overhead ISR feed PyRapide directly. Officers see causal chains across kinetic, non-kinetic, and electronic effects in near real time. White cell retains override authority over agent recommendations.

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03Tier

Forward Deployed

Hardened Edge Tier

For environments where Python and the cloud are not options. TRL-9 posture, scanner-clean, cATO-ready.

  • Everything in Live Augmentation, plus —
  • GoRapide single-binary engine for on-device DAG
  • Air-gap-ready offline EPSS / KEV / NVD feed cache
  • SCAP- and STIG-hardened images via the ACTA ATO readiness tool
  • Scanner-clean against grype, trivy, and anchore on every build
  • ACTA-emitted XML + YAML artifacts (POA&M, STIG CKL, NIST 800-53) for ATO and continuous ATO (cATO) CI/CD
  • DISA Container Image Creation Guide compliance
  • Iron Bank pipeline-compatible base images
  • C++ / Rust event trigger bindings for low-level integration
Who it's for

Tactical edge deployments on hardware or firmware that cannot host the Python kernel. The GoRapide engine variant ships as a single binary with offline feed cache. ACTA — the Authority To Operate (ATO) readiness tool — hardens every container image to SCAP and STIG baselines, certifies clean against grype, trivy, and anchore, and emits machine-generated XML and YAML artifacts that drop directly into ATO and continuous ATO (cATO) CI/CD pipelines.

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◆ FAQS ◆

Common questions about Almighty.

  • A causal event analysis engine for wargaming, exercise control, and live-fire training. Built on PyRapide. Forward-deployable. ACTA-hardened to TRL-9 posture.

  • Almighty was created at the Special Competitive Studies Project (SCSP) hackathon by Shane Morris, Devin Hill, and Alex Curnow. It was not a Dynamo product before the hackathon. It is now engineered, deployed, and supported by Dynamo Technologies.

  • Exercise controllers, white cell operators, and the engineering teams supporting joint training, combined arms, and Multi-Domain Operations (MDO) exercises across DoD and the broader U.S. defense community.

  • A timeline tells you what happened in the order it happened. A directed acyclic graph tells you why each step happened in that order. PyRapide records each event's causal predecessors, so an electronic warfare effect that ripples into a kinetic outcome is queryable as a chain — not reconstructed by hand. The white cell sees the chain of decision, not just the chain of outcomes.

  • CrewAI agents — blue battalion, red Opposing Forces (OpFor), and the white cell adjudicator — use the native PyRapide connector to subscribe to the kernel DAG. As the kernel commits new causal events, agents consume the updated graph immediately and adapt their next moves against it in real time. The override gateway sits between the agent runtime and the DAG with three policy scopes; the white cell retains authority over irreversible effects.

  • Almighty is fielded at Technology Readiness Level 9 (TRL-9) posture. Container images are SCAP- and STIG-hardened by ACTA and pass clean against grype, trivy, and anchore. Builds emit machine-generated XML and YAML artifacts — POA&M, STIG CKL, NIST 800-53 control assessments — sized for direct CI/CD integration into ATO and continuous ATO (cATO) pipelines.

  • Yes. The same PyRapide kernel that runs synthetic rehearsals accepts live device telemetry through Distributed Interactive Simulation (DIS) and High-Level Architecture (HLA) adapter contracts. Capability profiles validate every action against what the device can actually do. The white cell retains override authority.

  • A Go reimplementation of the PyRapide kernel that ships as a single binary with an offline feed cache. It exists for hardware and firmware environments that cannot host Python. Event triggers can be written in Go, C++, or Rust for low-level integration.

  • Almighty container images are hardened with ACTA — the ATO readiness tool — which produces SCAP- and STIG-compliant images that pass clean against grype, trivy, and anchore scanners. ACTA emits eMASS-importable POA&M CSVs, STIG CKL XML, and NIST 800-53 control assessments as machine-readable XML and YAML on every build, sized for cATO CI/CD pipelines so an Information System Security Manager (ISSM) can fold them into Authority To Operate (ATO) workflows directly.