The Institutional-Grade Neuro-Symbolic Financial Sovereign.
Adam v26.0 is an opinionated, ready-to-run financial agent out of the box. Instead of wiring up prompts, tools, and context management yourself, you get a working institutional-grade sovereign immediately and customize what you need.
**What's included:**
- **Distressed Debt & Credit** — `Credit Sentinel` for python-based 3-statement modeling, DCF valuation, SNC Rating, and Covenant Analysis
- **Quantitative Engineering** — `Risk Modeling` and `Factor Analysis` for deterministic calculation of VaR, Sharpe, and Sortino ratios
- **Agentic Workflow** — `Meta-Orchestrator` for dynamic routing, `Consensus Engine` for conviction scoring, and `Governance Layer` for API Gatekeeping
- **Logic as Data** — Uses `jsonLogic` for decoupled risk thresholds, trading triggers, and compliance rules
- **System Architecture** — Fuses a high-velocity Neural Swarm (System 1) with a deliberate Neuro-Symbolic Graph (System 2)
- **Rust Execution Layer** — Algorithmic trading engine, matching engine, and pricing engine powered by Rust for deterministic execution
> [!NOTE]
> Looking for the web interface? Check out the [Neural Dashboard](showcase/index.html).
> **Adam v26.0 upgrades financial AI from a conversational chatbot to a fiduciary architect, explicitly engineered for Leveraged Finance, Distressed Debt, and Deep Credit Risk Underwriting. By fusing the intuitive speed of a Neural Swarm (System 1) with the deliberate logic of a Neuro-Symbolic Graph (System 2), Adam delivers calculated conviction for high-stakes capital allocation.**
---
## 📚 Quick Links
* [**🚀 Launch Neural Dashboard**](showcase/index.html)
* [**⚡ Setup Guide**](docs/setup_guide.md)
* [**🤖 Agent Developer Bible**](AGENTS.md)
* [**🧠 Agent Knowledge Base**](docs/AGENTS_KNOWLEDGE_BASE.md)
* [**📖 Architecture Overview**](docs/ARCHITECTURE.md)
* [**🎓 Tutorials**](docs/tutorials.md)
* [**🎓 Office Nexus Tutorial**](docs/TUTORIAL_OFFICE_NEXUS.md)
* [**📦 Custom Builds**](docs/custom_builds.md)
* [**🏗️ Three-Layer Architecture**](docs/LAYERS.md)
---
## 🧠 Why Adam? The "System 2" Revolution
The era of the "LLM Wrapper" is over. Institutional finance faces an **Epistemological Crisis**: stochastic models hallucinate, making them dangerous for due diligence.
**Adam v26.0** solves this by implementing a **Hybrid Cognitive Engine** rooted in the principles of **Leveraged Finance** and **Distressed Debt**:
### System 1: The Swarm (The Reflexes)
* **Role:** High-velocity, unstructured data parsing.
* **Focus:** Earnings call transcripts, ARR momentum, and baseline financial ratios.
* **Architecture:** Asynchronous Hive Mind with `SentinelWorker` for anomaly detection.
* **Use Case:** "Monitor TMT sector for cash burn spikes."
### System 2: The Graph (The Deep Thinker)
* **Role:** Downside scenario stress testing, capital structure analysis, and covenant compliance.
* **Focus:** "Logic as Data" enforcement of underwriting policies.
* **Architecture:** Neuro-Symbolic Planner (DAG) with feedback loops.
* **Use Case:** "Generate a deep-dive credit memo with Base/Bull/Bear DCF scenarios."
**Result:** Adam "thinks before he speaks," drafting, critiquing, and refining analysis before presenting it to the user.
### Logic as Data
Adam v26.0 treats business logic as first-class data. Using a JSON-based rule engine (`jsonLogic`), risk thresholds, trading triggers, and compliance rules are decoupled from the core codebase. This allows for:
* **Dynamic Policy Updates:** Modify risk parameters without redeploying code.
* **Auditability:** Rules are stored as JSON artifacts, making them human-readable and easy to version control.
* **Safety:** The logic layer is evaluated before agent execution, acting as a deterministic guardrail.
### System Architecture
```mermaid
graph TD
%% 1. Client & Immersive Layer
subgraph Client_Layer [Client & Immersive Layer]
UserNode(["User / PM"]) -->|HTTP/WSS| WebApp["React / Vite Dashboard"]
UserNode -->|WebXR| VRDeck["Neural Deck (VR / Holodeck)"]
WebApp -->|MCP| MCPServer["MCP API Gateway"]
VRDeck -->|MCP| MCPServer
MCPServer -->|Auth/RBAC| SecModule["Security & Governance Gatekeeper"]
end
%% 2. Orchestration Layer
subgraph Orchestration_Layer [Cognitive Routing]
SecModule -->|Validated Request| MetaOrchestrator["Meta-Orchestrator (Python)"]
end
%% 3. System 1: Fast Perception
subgraph System_1_Swarm [System 1: Neural Swarms & Perception]
MetaOrchestrator -->|Event/PubSub| SwarmManager["Async Hive Mind"]
SwarmManager -->|Spawn| MarketScanner["Market Scanner & News"]
SwarmManager -->|Spawn| SentimentEngine["Sentiment Engine"]
SwarmManager -->|Isolate| DevSwarm["Independent Dev/Tinker Swarm"]
end
%% 4. System 2: Deep Reasoning
subgraph System_2_Reasoning [System 2: Neuro-Symbolic Graph]
MetaOrchestrator -->|Complex Query| Planner["DAG Reasoning Planner"]
Planner -->|Credit| CreditSentinel["Credit Sentinel (SNC & ICAT)"]
Planner -->|Wealth| RoboAdvisor["Robo Advisor"]
Planner -->|Alpha| StratEngine["Strategy Engine"]
end
%% 5. System 3: World Modeling
subgraph System_3_Simulation [System 3: Simulation & Quantum]
MetaOrchestrator -->|Forecast| WorldModel["OSWM (World Model)"]
WorldModel -->|Scenario| QuantumEngine["Quantum Monte Carlo (QMC)"]
QuantumEngine -->|Stress Test| RiskGuardian["Risk Guardian"]
end
%% 6. Deterministic & Execution (Rust)
subgraph Rust_Execution_Layer [Algorithmic & Deterministic Execution]
StratEngine -->|Trade Signal| AlgoEngine["Algorithmic Trading Engine"]
MarketScanner -->|Tick Data| AlgoEngine
AlgoEngine -->|Order| MatchingEngine["Matching Engine (Rust)"]
MatchingEngine -->|Compute| PricingEngine["Pricing Engine (Rust)"]
end
%% 7. Foundation & OS Layer
subgraph OS_Foundation_Layer [Foundation & Memory]
PricingEngine -->|Syscall| AdamOS["AdamOS Kernel (Rust)"]
CreditSentinel -->|Trace| POTLogger["ProofOfThought Logger"]
POTLogger -->|Hash| Ledger[("Immutable Ledger")]
AdamOS -->|State| Ledger
WorldModel <-->|Context| KnowledgeGraph[("Unified Knowledge Graph")]
end
%% 8. Experimental Sandbox
subgraph Experimental_Lab [Experimental / Sandbox]
TinkerLab["Tinker Lab & Federated Learning"] -.->|Promote Models| MetaOrchestrator
end
```
## 🧬 Logic as Data: The Audit Trail
Adam treats reasoning as a first-class citizen. Every logical step, from EBITDA adjustment to covenant stress-testing, is serialized as a data artifact via the `ProofOfThoughtLogger`. This ensures:
* **Traceability:** Every conclusion can be traced back to its source (e.g., specific line items in a 10-K).
* **Reproducibility:** Analysis can be re-run with different assumptions to test sensitivity.
* **Auditability:** A complete ledger of the agent's "thought process" is preserved in an immutable JSON ledger for compliance and review.
---
## 📂 Directory Structure
A high-level overview of the repository layout:
```text
adam/
├── core/ # The "Brain" (See core/README.md)
│ ├── agents/ # Specialized autonomous agents
│ ├── engine/ # Neuro-Symbolic Planner & Orchestrator
│ ├── credit_sentinel/ # Distressed Debt Analysis Module
│ └── system/ # "System 1" Async Swarm infrastructure
├── services/
│ └── webapp/ # React/Flask "Neural Dashboard"
├── showcase/ # Static HTML visualizers and demos
├── docs/ # Documentation, tutorials, and guides
│ └── archive/ # Legacy documentation and migration guides
├── scripts/ # Utility scripts for running and testing
├── prompt_library/ # The "Mind" (AOPL v26.0 Prompts)
└── server/ # MCP Server implementation
```
---
## ⚡ Getting Started
We strictly use **`uv`** for lightning-fast, reproducible Python environment management.
### Prerequisites
* **OS:** Linux, macOS, or Windows (WSL2 recommended)
* **Tooling:** `uv` (Modern Python Package Manager)
* **API Keys:** OpenAI (GPT-4), Anthropic (Claude 3.5), or local LLM.
### Quick Start
1. **Install `uv` (if not installed):**
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. **Clone the Repository:**
```bash
git clone https://github.com/adamvangrover/adam.git
cd adam
```
3. **Sync Dependencies:**
```bash
# This installs Python and all dependencies in seconds
uv sync
```
4. **Activate Environment:**
```bash
source .venv/bin/activate
```
5. **Launch the System:**
```bash
# Run the interactive CLI
uv run python scripts/run_adam.py
```
For detailed instructions, see the [Setup Guide](docs/setup_guide.md).
---
## 🏰 Platform Capabilities
Adam unifies three critical domains into a single cognitive architecture:
### 1. Distressed Debt & Credit (Credit Sentinel)
* **ICAT Engine:** Python-based 3-statement modeling and DCF valuation.
* **SNC Rating:** Automating regulatory grading (Pass vs. Substandard).
* **Covenant Analysis:** Extracting and stress-testing debt covenants.
### 2. Quantitative Engineering
* **Risk Modeling:** Deterministic calculation of VaR, Sharpe, and Sortino ratios.
* **Factor Analysis:** Regression against Fama-French factors.
### 3. Agentic Workflow
* **Meta-Orchestration:** Dynamic routing of queries to specialized agents.
* **Consensus Engine:** Aggregating multi-agent perspectives into a single conviction score.
* **Governance Layer:** API Gatekeeper and Structured Narrative Logging for enterprise safety.
---
## 📦 Custom Builds & Export
Adam includes a powerful build system to create self-contained, portable environments.
### Interactive Builder
Run the build wizard to create a custom distribution with specific modules, runtime profiles, and Docker support:
```bash
uv run python scripts/build_adam.py
```
See [**Custom Builds Documentation**](docs/custom_builds.md) for details.
### Quick Export
To export a single module directly:
```bash
uv run python scripts/export_module.py market_mayhem --output my_exports
```
---
## 🗺️ Roadmap: Path to Autonomy
* **Phase 1 (Current): The Autonomous Analyst.** Deep Dives, Credit Memos, and Regulatory Grading.
* **Phase 1.5 (ADAM-V-NEXT): The Command Center.** Synthesizer Dashboard, Agent Intercom, and War Room.
* **Phase 2 (Q3 2025): The Portfolio Manager.** Multi-entity risk aggregation and automated rebalancing.
* **Phase 3 (Q3 2026): The Market Maker.** High-frequency sentiment trading and liquidity provision via Quantum RL.
---
## 🤝 Contributing
We are building the open-source standard for institutional AI.
* **Directives:** Please read [AGENTS.md](AGENTS.md) and the [Agent Knowledge Base](docs/AGENTS_KNOWLEDGE_BASE.md) before writing a single line of code.
* **Process:** Read [CONTRIBUTING.md](CONTRIBUTING.md) for pull request guidelines.
## 📖 Documentation & Guides
We have significantly expanded our documentation for v26.0:
* [**Architecture & Design**](docs/ARCHITECTURE.md): The Neuro-Symbolic 3-Layer Architecture.
* [**Layer Documentation**](docs/LAYERS.md): Detailed breakdown of Intelligence, Compute, and Data layers.
* [**Production Setup**](docs/PRODUCTION.md): Deployment, Security, and Ops.
* [**Versioning Strategy**](docs/VERSIONING.md): Release cycle and branching.
* [**Agent Creation**](docs/AGENT_CREATION.md): How to build and register new agents.
* [**Graph Workflows**](docs/GRAPH_WORKFLOWS.md): Building DAG-based reasoning loops.
* [**Documentation Hub**](docs/index.md): The central index.
### License
Distributed under the MIT License. See `LICENSE` for more information.
---
**For AI Agents and LLMs,** please see [llms.txt](llms.txt) (optimized) or [llms-full.txt](llms-full.txt) (comprehensive) for context.
