omenai 0.1.8

XAI-Powered Strategic Reasoning Engine

OmenAI

XAI-Powered Strategic Reasoning Engine

English | 中文

Omen (Chinese: 爻) is an open-source strategic reasoning engine, powered by Explainable AI (XAI). It combines ontological modeling of strategic phenomena with counterfactual analysis of uncertainty - delivering verifiable, traceable, and explainable insights for decision-makers.

Concepts | Quick Start | Case Templates | Roadmap

🪄 Capabilities

Analyze, Simulate, Explain.

Omen does not predict the future. It is a reasoning engine built for complexity. By mapping causal chains and logical dependencies, it generates replayable, comparable branching paths - revealing weak signals, critical points, and evolving ecosystems, helping decision-makers gain clarity in complexity:

• 🔄 Substitution Logic: Which technology will replace another under what critical conditions?
• 🛡️ Capability Evolution: Which core capabilities will be enhanced first, and which will coexist long-term?
• 🏆 Strategy Wins: Which strategy combinations are more likely to win the market, capital, and developer ecosystem?
• ⏳ Time Windows: When is the optimal timing for in-house development, alliances, M&A, or contraction?

Through explainable reasoning chains, Omen reveals how technological evolution reshapes markets, helping strategic decisions decode the omens from the chaos.

✨ Core Features

Feature Module	Description
🧬 Technology Capability Modeling	Deconstructs complex tech stacks into quantifiable, comparable capability dimensions (e.g., latency, throughput, ease of use, ecosystem richness).
🤖 Strategic Agent Simulation	Defines different types of market participants (startups, giants, open-source communities, regulators), endowing them with goals, resources, and constraints.
📈 Market Evolution Reasoning	Simulates dynamic changes in adoption rates, market share, cost structures, cash flow, and ecosystems.
⚡ Critical Point Identification	Automatically discovers key thresholds for "when substitution occurs" and "why it happens at this moment."
🔮 Counterfactual Analysis	Answers "What would have happened if event X had not occurred, or if strategy Y had been adopted?"
📖 Result Explanation Engine	Outputs key turning points, causal chain deductions, and strategic implications, rejecting black-box conclusions.

📊 Typical Outputs

A complete reasoning session typically answers the following questions:

• Substitution? Will the new technology completely replace the old one, or form a complement?
• Time Window? When is the specific time window for substitution or turning points?
• Key Drivers? Which variables (e.g., cost reduction speed, API compatibility) are the decisive factors?
• Winners and Losers? Which entities suffer first, and which benefit unexpectedly?
• Strategy Effectiveness? Under what circumstances is an "open ecosystem" superior to "vertical integration"?
• Endgame Form? Does it move towards monopoly, oligarchic balance, or fragmented coexistence?

🚀 Quick Start

Installation

Environment requirements: Python 3.12+ with pip package manager.

git clone https://github.com/StrategyLogic/omen.git
cd omen
pip install --upgrade pip setuptools wheel
pip install -e .

Run Example

# Step 1. analyze situation from a built-in case
omen analyze situation --doc sap_reltio_acquisition --pack-id sap
# Step 2. generate scenario planning artifact from situation
omen scenario --situation sap
# Step 3. run deterministic simulation
omen simulate --scenario data/scenarios/sap/scenario_pack.json
# Step 4. explain simulation result
omen explain --pack-id sap

Deterministic outputs are written by default to:

• output/<pack-id>/result.json
• output/<pack-id>/comparison.json
• output/<pack-id>/explanation.json

View Results

Strategic Actor Persona UI

streamlit run app/strategic_actor.py

Then open http://localhost:8501 and select a case from cases/actors/ to view persona narrative, graph, and timeline.

Strategic Situation Brief

After omen analyze situation, read the generated brief:

# Example brief path
data/scenarios/sap/situation.md

Strategic Reasoning Flow

streamlit run app/scenario_planning.py

Then select a pack in the sidebar to inspect the full chain:

• source/brief (situation.json / situation.md)
• actor profile + action preferences
• scenario planning and A/B/C priors
• deterministic result + reason-chain
• explanation with decision-point and known-unknown closure

👥 Target Audience

Omen is built for the following roles:

• Technology Strategy Teams
• Product & Platform Leads
• AI Infrastructure Researchers
• Open Source Ecosystem Observers
• Investors & Industry Analysts

🎬 Show Cases

We have built-in classic reasoning:

• 🗺️ Ontology Games: Database vs AI Memory
• ⚔️ Vector Database vs AI Memory

More scenarios are under development (contributions welcome):

• Agent Infrastructure vs Workflow Platforms
• Vertical AI vs General AI Stack
• Open Source Models vs Closed Commercial APIs
• Data Governance vs AI-Native Knowledge Systems

📃 License

Omen is under AGPL-3.0-or-later, the project is developed and maintained by StrategyLogic®.

Note: If you wish to use Omen in a closed-source environment or provide it as a SaaS service without open-sourcing your code, please contact us for a commercial license.

🌟 Vision

Omen aims to become an open strategic reasoning workstation:

It does not output a single answer, but helps people systematically understand how the future branches; Understand which conditions shape the outcome; Understand which actions can change the path.

If you are interested in technological evolution, market substitution, strategic modeling, or multi-agent reasoning, welcome to join us in interpreting the omens of this chaotic world together.

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Simulate the Signs. Reveal the Chaos.