A production-oriented, full-stack architecture for secure, coalition-aware, latency-sensitive intelligence operations that ingest live and historical data, reason over a governed ontology, learn from operator feedback, and propose safe self-upgrades under explicit human approval.
Operator surfaces connect through a policy-aware API gateway into deterministic mission services, event streaming, AIP orchestration, Foundry/Gotham operational data, hybrid retrieval, observability, and Apollo runtime control.
Frontend → API Gateway → Mission Services
→ Kafka/Flink Events → AIP Agents
→ Foundry Ontology + Gotham Graph
→ Policy + Audit + Apollo Release RingsThe ontology models missions, actors, assets, observations, alerts, cases, actions, intel products, feedback, model routes, and improvement proposals with confidence, lineage, temporal state, and permissions.
Mission ─ scopes ─ Case ─ contains ─ Alert Actor ─ linked_to ─ Asset ─ emits ─ Observation AgentRun ─ cites ─ Evidence ─ derives ─ IntelProduct
Investigations, entity tracking, link analysis, case timelines, mission collaboration, and analyst workflows.
Ingestion, pipelines, data products, lineage, Ontology objects, object actions, and governed application logic.
Copilots, tool-using agents, evaluations, prompt governance, model routing, and workflow automation over approved data/actions.
Signed releases, progressive deployment, policy bundles, rollback, feature flags, and environment-specific controls.
Need-to-know, entity-level controls, coalition compartments, prompt/tool policy, and immutable authorization logs.
Metrics, traces, model telemetry, eval scorecards, drift monitors, lineage, and operator trust signals.
if evals.pass_all() and human_approval.granted:
apollo.promote(candidate, ring="canary")
else:
registry.pin(current_known_good)Analyst and commander copilots coordinate triage, enrichment, correlation, summarization, recommendation, product generation, case opening, and action-package drafting. Operationally significant actions require explicit human approval gates.
Row, column, entity, and action-level access control; compartmentalized retrieval; provenance-linked prompts; immutable logs; model governance; and policy-as-code enforced before every data read, tool call, and release.
Artemis now includes a reusable defensive-algorithm operating prompt for AIP copilots, triage agents, policy agents, and CI/CD guardians. It prioritizes safety, containment, verification, least privilege, evidence preservation, reversible actions, and explicit human approval for identity, credential, production, or high-impact events.
Low risk → observe and log Medium risk → warn, constrain, verify High risk → isolate, halt, escalate Critical risk → contain, preserve evidence, notify operators
A downloadable PowerShell utility has been added for elevated Windows workstations. It creates a desktop registry backup folder before applying Hardware-Accelerated GPU Scheduling, TDR delay, Ultimate Performance power-plan, SystemProfile, network-throttling, and MMCSS Games scheduling tweaks. Run only from an Administrator PowerShell session and restart after completion.
Set-ExecutionPolicy -Scope Process Bypass .\tools\windows\ultimate-windows-gpu-advanced-graphics-optimization.ps1
A safer PowerShell alternative now keeps the original enthusiast script intact while adding explicit guardrails: registry exports, JSONL value snapshots, per-action logging, verified Ultimate Performance activation, optional HAGS enable/disable, opt-in TDR troubleshooting, opt-in SystemProfile/MMCSS experiments, WhatIf previews, and rollback from the generated backup folder.
powershell -ExecutionPolicy Bypass -File .\tools\windows\safe-windows-gpu-tuning.ps1 -ApplyLowRisk powershell -ExecutionPolicy Bypass -File .\tools\windows\safe-windows-gpu-tuning.ps1 -ApplyLowRisk -IncludeTdrDelay -WhatIf
Artemis now models electrical inspections as permit-aware, evidence-backed work orders: immediate hazards are isolated first, qualified electricians perform de-energized LOTO work, circuits are traced and labelled, test evidence drives closeout, and verified findings become customer-ready estimates, maintenance plans, and recurring revenue workflows.
Finding → severity classifier → controls + permit gate
→ work order → test register → final report
→ quote / maintenance plan / revenue metrics