ScenarioForge

Gemini LLM Advisor- grounded in run data. Ask about entity, geography or strategy
Tool Configuration- Default is good
EBE Driving Force- What influence the future
Run Control- Command Center
Run Overview- Track details and nodes
Create New Run- Enter entity and keep everything else default or modify
Scenarios and Images Created by Gemini
Wind Tunnel- Strategy Analysis, sorting and actions plan by Gemini
Wind Tunnel- How Strategies fair per per Scenario

Gemini 3 Integration Overview

ScenarioForge is built around Gemini 3’s advanced reasoning and multimodal capabilities, which are central to its function as a live strategy workspace rather than a static analysis tool.

Gemini 3 is used for multi-step causal reasoning across signals, scenarios, and strategies, enabling the system to evaluate how strategic options perform under multiple plausible futures. This allows ScenarioForge to identify resilience, fragility, and assumption breakpoints rather than producing surface-level summaries.

The model’s long-horizon coherence is critical for maintaining consistency between evidence, assumptions, scenarios, and recommendations across repeated strategy review cycles. This ensures outputs remain auditable and comparable over time.

ScenarioForge also leverages Gemini 3’s multimodal generation to create visual representations of scenarios. These images complement narrative scenarios and improve executive comprehension by making future states tangible and easier to reason about.

In addition, Gemini 3 powers a data-grounded strategy advisor. Unlike a generic chat interface, this advisor is strictly constrained to the collected evidence and generated scenarios, enabling structured questioning, comparison, and exploration without speculative drift.

Finally, low-latency streaming of intermediate reasoning outputs allows transparency and trust, supporting real-time interaction within the strategic workflow.

Together, these Gemini 3 features enable ScenarioForge to operate as a continuously updated, evidence-driven strategic command system.

Built With

agent-based
apis
cli
cloud-run
fastapi
google
html
javascript
json
markdown
orchestration
python
vector-databse
web-search

Submitted to

Gemini 3 Hackathon

Created by

I designed, built, and implemented ScenarioForge end-to-end as a solo developer.

My contribution covers the full system lifecycle: defining the strategic problem, translating MBA-level scenario planning frameworks into deterministic workflows, designing the orchestration architecture, and implementing the full pipeline in Python.

I integrated Gemini 3 as a core reasoning and multimodal engine, using it for evidence synthesis, multi-step causal reasoning across scenarios and strategies, visual scenario generation, and a data-grounded strategy advisor constrained to validated inputs. I also implemented streaming interactions to support transparency and real-time strategic exploration.

Beyond the technical build, I structured the system to support continuous strategy review (quarterly or bi-annual), auditability, and governance—addressing a real gap between traditional consulting-led strategy cycles and the pace of environmental change.

The project demonstrates how a single practitioner, augmented by modern AI tooling, can operationalize institutional-grade strategy work into a living, continuously updated strategic system.

Abdul Jalil Shreim

Updates

Abdul Jalil Shreim started this project — Jan 30, 2026 08:47 AM EST

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