StratCommand

Inspiration

I was inspired by the gap between raw financial data and the human narratives that drive boardroom decisions. In most companies, financial auditing is reactive and manual. I wanted to build a proactive "Marathon Agent" that doesn't just read spreadsheets but "reads the room," cross-referencing verbal stakeholder commitments with digital ledgers to identify risks that human auditors often miss.

What it does

StratCommand is a high-fidelity Strategic Oversight tool. It ingests complex financial documents (CSVs, XLSX, PDFs) and boardroom audio/video to provide:

• Autonomous Auditing: A self-correcting loop that writes and executes Python logic to verify every cent before updating the dashboard.
• Vibe Engineering: Using Gemini 3’s multimodal senses to detect "Narrative Mismatches" identifying when executive sentiment contradicts the hard data in the company ledger.
• Strategic Command: A real-time dashboard showing liquidity ratios, burn rates, and risk exposure, all backed by a transparent "Thought Signature" log that proves the agent’s reasoning.
• Executive Artifacts: Instant generation of "Verified Briefing PDFs" for board distribution, ensuring one source of truth.

How we built it

I utilized a multi-model architecture within Google AI Studio:

• Gemini 3 Flash: Used for the low-latency UI components, chart rendering, and real-time feed synchronization.
• Gemini 3 Pro: The "Brain" of the system, handling high-level reasoning, complex data analysis, and the Action Era tool-calling loops.
• Vibe Coding Workflow: I leveraged the Antigravity Public Preview and AI Studio Build tab to orchestrate specialized agents.
• Python Tool-Calling: Every fiscal chart is the result of an internal Python verification script, fulfilling the requirement for autonomous testing loops.

Challenges we ran into

Implementing the Antigravity agentic IDE was a major hurdle. Faced several "Agent loading" loops and local configuration conflicts that required deep-diving into task-manager processes and clearing local AppData caches. Additionally, ensuring that the Gemini 3 Pro agent correctly translated its internal Matplotlib logic into high-fidelity JSON artifacts for the StratCommand UI required careful prompt engineering to resolve data-binding conflicts.

Accomplishments that we're proud of

I'm incredibly proud of the Strat-Gen Reasoning Core. It isn't just a log; it’s a transparent Thought Signature that shows the AI planning, executing code, finding its own errors, and self-correcting. Achieving a professional "Command Center" aesthetic that feels like an enterprise tool while being powered entirely by agentic AI is a major milestone for us.

What we learned

I learnt that in the Action Era, orchestration is more important than prompting. Moving from a single-turn chatbot to a multi-step agentic system required us to rethink how I "Vibe Code." I discovered that Gemini 3’s greatest strength isn't just knowing the answer, but its ability to use tools to prove the answer is correct.

What's next for StratCommand

• Live Multimodal Integration: Moving from recorded meeting analysis to real-time, live-streamed boardroom auditing via the Gemini Live API.
• Predictive "What-If" Simulations: Allowing CFOs to ask the agent to run 1,000 autonomous market simulations to test the resilience of their current cash flow forecast.
• Decentralized Ledger Sync: Connecting StratCommand directly to ERP systems like SAP and Oracle for real-time, 24/7 autonomous fiscal monitoring.

Built With

• gemini-3-flash
• gemini-3-pro
• google-ai-studio
• tailwindcss
• typescript