Strategic Advisory Guidance Engine

TRL 7 — Operational Prototype Alpha · Moving to Beta

From months of analysis
to minutes.

SAGE is a working AI decision-support system that compresses cross-domain national strategy analysis from days or months down to minutes — without losing the methodological substrate that makes the conclusions defensible.

SAGE — Demonstration

What SAGE Produces

Four outputs, one engagement

Each SAGE engagement produces a structured set of deliverables designed to move a strategic question from open enquiry to actionable policy direction — with every claim traceable to its analytical source.

Quantified influence scoring

DIME-framework scoring across diplomatic, informational, military, and economic instruments — calibrated to the specific strategic context rather than generic templates.

Second- and third-order effects

Mapped interaction effects across instruments and actors, surfacing downstream consequences that linear analysis routinely misses.

III

Three modeled courses of action

Generated across an assertiveness spectrum with modeled political support — giving decision-makers a defensible range rather than a single recommended path.

Implementation roadmap

Named lead agencies, sequenced milestones, and projected influence trajectories — translating strategy into the institutional language of execution.

Methodology & Authority

Defensible by design

SAGE is built on the DIMEFIL-DC ontology and a National Power Index (NPI) knowledge base, both authored and governed by the Center for the Application of Grand Strategy. Influence scoring, interaction modeling, and course-of-action generation all operate against this substrate — not against an undocumented model interior.

Output is shaped by a multi-agent pipeline running on Google Cloud, engineered by VerbaAI. Each agent has a defined analytical role, and intermediate reasoning is preserved for review rather than collapsed into a single answer.

Three Human-in-the-Loop Checkpoints

Problem framing. The strategic question, scope, and adversary/actor set are confirmed before scoring begins.

ii.

Influence calibration. DIME scores and identified interaction effects are reviewed against expert judgment before COA generation.

iii.

Course-of-action selection. The decision-maker selects among the three modeled COAs and authorises the implementation roadmap. Authority is preserved with the human, not the system.

Built In Partnership

Methodology, engineering, delivery

SAGE is built by Valexis Global in close collaboration with two essential partners — one governing the methodological substrate, one delivering the engineering platform.

Methodology Authority

Center for the Application of Grand Strategy

CAGS authors and governs the DIMEFIL-DC methodology and the National Power Index knowledge base that underpin every SAGE output.

cagsai.org Nick Kesler, Principal

Engineering Partner

VerbaAI

VerbaAI delivers the multi-agent pipeline and platform infrastructure on Google Cloud — the engineering layer that makes minute-scale analysis repeatable and inspectable.

verbaai.org

Product & Delivery

Valexis Global

Valexis Global integrates the methodology and platform into a delivered product, owns the client engagement, and operates the alpha-to-beta test & evaluation programme toward TRL 7 attestation.

About the Firm Request a Briefing

A note on structure. Methodology is governed by CAGS as an applied research organisation; the platform is engineered by VerbaAI; the product is delivered by Valexis Global. This separation is intentional — it keeps the analytical substrate independent of any single commercial interest, including our own.