Mission Cadre

What we deliver

Production-grade IT and AI engineering.

Five practice areas structured around the FAB framework — Feature, Advantage, Benefit — so every technical capability maps directly to a business outcome.

01
Agentic AI Platforms

Agentic AI Platforms

Institutional agent platforms with shared connectors, policy engines, and full governance.

F
Feature

A multi-agent orchestration platform with shared connectors, a unified tool registry, a central policy engine, and governance-enforced execution logs — deployable on your cloud or on-premise.

A
Advantage

Moving beyond standalone AI agents eliminates duplicated integration work, removes security blind spots, and creates a single control plane for all autonomous workflows.

B
Benefit

Get new agents off the ground in days instead of months. Reduce operational risk. Cut integration costs by 60–80% through shared connectors. Demonstrate AI governance to auditors and boards.

Typical outcomes

  • 60% reduction in manual proposal and workflow processing
  • 10× faster deployment of new agent capabilities
  • 100% audit coverage for all agent-executed decisions
  • 8 weeks average to first production-grade agent

Technology

LangGraph / CrewAIPolicy engine200+ enterprise connectorsAudit dashboardSelf-healing workflows
02
Enterprise Data Infrastructure

Enterprise Data Infrastructure

Semantic layers, Lakehouse foundations, and data contracts that give AI something reliable to reason over.

F
Feature

An independent semantic layer on a modern Lakehouse foundation (Delta Lake / Iceberg), with dbt-modelled data products, Great Expectations quality gates, lineage tracking, and unified metric definitions.

A
Advantage

Eliminating semantic drift removes the reconciliation work consuming analyst time, causing AI hallucinations, and eroding trust in reporting. One source of truth enables reliable AI reasoning.

B
Benefit

Cut 40% of analyst time wasted on data reconciliation. Sub-second semantic queries at petabyte scale. An AI-ready data substrate every future agent can trust.

Typical outcomes

  • 40% reduction in analyst reconciliation time
  • 99.9% data quality SLA across semantic layer
  • <1s query latency at petabyte scale
  • 12 weeks to production-ready Lakehouse

Technology

Delta Lake / Apache Icebergdbt CoreGreat ExpectationsApache AtlasDatabricks / Snowflake
03
Cloud & IT Strategy

Cloud & IT Strategy

Architecture reviews, technology roadmaps, and cloud strategy aligned to your business objectives.

F
Feature

End-to-end technology advisory covering cloud architecture, vendor evaluation, infrastructure modernization, and IT operating model design — aligned directly to your business strategy.

A
Advantage

Unlike strategy-only firms, every recommendation is grounded in engineering reality. We build what we advise, so roadmaps are actionable, not aspirational.

B
Benefit

A clear technology roadmap with costed implementation paths, reduced technical debt, and an architecture your engineering team can execute and own.

Typical outcomes

  • Clear 12–24 month technology roadmap
  • Vendor selection frameworks with quantified trade-offs
  • Infrastructure cost reduction typically 20–35%
  • Architecture docs your team can act on immediately

Technology

AWS / Azure / GCPTerraform / PulumiKubernetesArchitecture Decision RecordsCloud cost modeling
04
Predictive AI FinOps

Predictive AI FinOps

Shift from reactive cost reports to continuous automated rightsizing that predicts inference spikes.

F
Feature

A continuous cost optimization engine using ML-driven anomaly detection, inference spike prediction, automated rightsizing recommendations, and real-time FinOps dashboards covering cloud compute, storage, and LLM inference costs.

A
Advantage

Proactive, automated optimization instead of monthly reactive reporting. The system identifies rightsizing opportunities before they become overruns and predicts spikes 72 hours ahead.

B
Benefit

20–35% reduction in cloud and AI inference spend within Q1. Eliminate surprise invoice spikes. Give your CFO real-time AI ROI visibility across every deployed workload.

Typical outcomes

  • 20–35% cloud and inference cost reduction in Q1
  • 72-hour advance warning on cost spikes
  • 100% real-time cost visibility per AI workload
  • $14M+ cumulative client cloud savings

Technology

Cost attribution engineML spike predictorAutomated rightsizingUnified cloud + SaaS viewCFO-ready reporting
05
Security

Security

End-to-end security engineering for commercial enterprises and government agencies — from zero-trust architecture to AI-specific threat modeling and regulatory compliance.

F
Feature

A comprehensive security practice spanning zero-trust network architecture, AI/ML threat modeling, SOC 2 and FedRAMP compliance engineering, penetration testing, SIEM deployment, identity and access management (IAM), supply chain security, and continuous vulnerability management — designed for both commercial and government environments.

A
Advantage

Most security consultancies deliver assessments and reports. We deliver working security infrastructure. Every recommendation is backed by engineering implementation, not just advisory documentation. Our team holds active clearances and has delivered security programs for both Fortune 500 organizations and federal agencies.

B
Benefit

A hardened security posture that satisfies commercial audit requirements (SOC 2, ISO 27001, GDPR) and government compliance frameworks (FedRAMP, NIST 800-53, CMMC, ITAR). Reduce your attack surface, achieve compliance faster, and build the trust that enterprise and government clients require.

Typical outcomes

  • Zero-trust architecture deployed and operational in 10–14 weeks
  • SOC 2 Type II or FedRAMP readiness achieved in a single engagement
  • AI/ML threat model covering all deployed agent and inference workloads
  • Mean time to detect (MTTD) reduced by 60–80% through SIEM tuning
  • Full CMMC Level 2/3 compliance for defense contractor environments

Technology

Zero-trust / ZTNANIST 800-53 / CMMCFedRAMP / StateRAMPSIEM / SOC toolingIAM / PAMAI threat modelingPenetration testingITAR / EAR compliance

How we engage

Three commercial structures.

All include the Technical Sovereignty Guarantee — full code, model, and data handoff with no ongoing dependency.

Sprint Engagement
8–12 weeks
Pilot to production
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Embedded Engagement
3–6 months
Complex transformation
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Advisory Engagement
Monthly
Post-handoff optimization
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Not sure which service fits?

In a 60-minute AI Opportunity Assessment our engineers will map your situation to the right service and scope.

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