Mission Control

Applied Research Systems

Purpose-built AI infrastructure engineered for audit-defensible governance, autonomous execution, and operational resilience. Six core modules spanning decision frameworks, multi-LLM orchestration, and workflow automation form the institutional backbone of BlackStack — every module operating under deterministic protocols with complete audit trails, governed escalation paths, and Big 4 methodology alignment across all 43 governed services.

NIST AI RMF ISO 42001 SOC 2 Compliant COBIT 2019

Authorized Access Required

Research Domains

Quantitative models and AI governance systems.

AI-Driven Financial Risk Analytics

Real-time portfolio risk assessment combining parametric VaR, historical simulation, and Monte Carlo methods — enhanced by ML models detecting non-linear tail dependencies. Portfolio-level Greeks across multi-asset positions with stress scenarios aligned to Basel III/IV and IFRS 9, calibrated against 6 years of production benchmarks.

VaR ModelsMonte CarloFair Value

Regulatory Compliance Automation

Automated compliance pipelines ingesting regulatory documents through RAG-powered extraction, mapping requirements to internal controls with evidence collection on defined cadences. Compliance-as-code encodes NIST AI RMF, ISO 42001, SOC 2, and COBIT 2019 as machine-readable policies with automated testing and remediation tracking.

NISTISO 42001SOC 2

Multi-Agent Financial Intelligence

Cooperative AI agents in a dispatcher architecture — LEDGER for financial analysis, CIPHER for forensic accounting, VIGIL for compliance — coordinated through Bridge Relay with Redis-based stigmergy. Asynchronous collaboration via shared state producing emergent coordination on complex financial tasks with audit trails and escalation paths.

Bridge RelayRedisSwarm

Decision Framework Engineering

Structured decision methodology built on eight maturity gates — pre-commit validation, automated testing, backup verification, dual-approval authorization, and immutable audit-trail logging. Decisions documented through RACI matrices capturing context, alternatives, risk assessment, and approval chains.

Maturity GatesRACICOBIT

Aligned with FSOC objectives and U.S. Treasury priorities for responsible AI adoption in financial services.

Operational Metrics

Infrastructure benchmarks and compliance data.

Auditable Code

Lines of Auditable Code

Production-grade codebase spanning 43 MCP servers, 16 agent specifications, and the full 8-layer architecture. Every line is version-controlled, audit-traceable through automated commit hooks, and validated by 10 pre-commit guards ensuring code quality, secret detection, and compliance.

0K+

Compliance Controls

Active governance controls implementing NIST AI RMF, ISO 42001, SOC 2, and COBIT 2019 frameworks. Each control encoded as machine-readable policy with automated testing cadences, evidence collection, remediation tracking, cross-reference validation, and continuous compliance monitoring.

MCP Servers

Server architecture organized across six operational tiers delivering 192+ specialized tools for engineering, operations, compliance, and financial analytics. Each server follows MCP protocol specifications with health monitoring, authentication gating, and request-response audit logging.

Governed AI Agents

Autonomous agents coordinated through Bridge Relay with deterministic dispatch routing, multi-level risk gates, and complete audit trails. The swarm includes dispatchers, specialized agents, and financial analysts — each under strict role-based permissions with governed escalation paths.

Operational Systems

Governed modules powering autonomous operations.

decision.py

class DecisionFramework:
  """Institutional risk governance"""

  def __init__(self):
    self.gates = 8
    self.framework = "NIST AI RMF"
    self.methodology = "RACI"
    self.approval = "dual-sign"

  def evaluate(self, decision):
    risk = self.assess(decision)
    if risk > self.threshold:
      return self.escalate(decision)
    return self.approve(decision)

  # Version-controlled audit trail

architecture.py

class AIArchitecture:
  """Multi-LLM orchestration engine"""

  def __init__(self):
    self.providers = 9
    self.mcp_servers = 43
    self.agents = 16
    self.tools = 192

  def dispatch(self, task):
    agent = self.route(task)
    model = self.select(task)
    return agent.execute(
      model=model, trace=True
    )
  # Bridge Relay v3.9 backbone

automation.py

class WorkflowAutomation:
  """Compliance automation engine"""

  def __init__(self):
    self.engine = "n8n"
    self.pipelines = 29
    self.protocol = "governed"
    self.mode = "autonomous"

  def execute(self, workflow):
    valid = self.validate(workflow)
    if not valid:
      return self.flag(workflow)
    return self.run(workflow)

  # Real-time exception handling

knowledge.py

class KnowledgeTransfer:
  """Governance framework training"""

  def __init__(self):
    self.certs = 41
    self.format = "1:1 sessions"
    self.domains = ["NIST", "SOC 2"]
    self.standard = "COBIT 2019"

  def assess(self, candidate):
    score = self.evaluate(candidate)
    if score >= self.threshold:
      return self.certify(candidate)
    return self.recommend(candidate)

  # Agentic AI deployment patterns

Technology Stack

Infrastructure and automation platforms powering our research systems.

Orchestration

Orchestration & Automation

n8n serves as our primary workflow orchestration engine with 7 MCP-integrated tools, automating compliance documentation, audit trail generation, and multi-agent coordination across the stack. Make and Zapier extend integration reach across 3,000+ SaaS connectors for CRM, communications, and data enrichment pipelines. Bridge Relay v3.9 with Redis stigmergy coordinates our 16-agent swarm, dispatching tasks across 9 AI backends with full trace logging.

Infrastructure

Infrastructure & DevOps

Docker containers isolate n8n, Redis, and Open WebUI services with persistent volumes and automated health monitoring across our infrastructure stack. GitHub provides version control, CI/CD pipelines, and code review workflows for 251K+ lines of governed code across the 8-layer architecture. Python and Node.js power 43 MCP servers, VS Code serves as the primary IDE, and Tailscale provides zero-trust mesh networking with WireGuard encryption.

The logos displayed represent tools and platforms used in internal workflows, system development, and research. They do not imply endorsement, partnership, or affiliation unless explicitly stated.