BoardBrief AI (Gemini 3)

• 

Inspiration

Security incidents are usually documented for engineers, not for executives. While security teams think in logs, alerts, and indicators, leadership needs clear answers: What is the impact? How urgent is this? What decisions need to be made now? This gap between technical incident reports and executive decision-making leads to delays, misaligned priorities, and unnecessary risk. BoardBrief AI was created to bridge that gap.

What it does

BoardBrief AI transforms a plain-text cybersecurity incident description into a board-ready executive brief in minutes.

Input:

A free-text description of a cybersecurity incident (copied from an email, ticket, or report).

Output (consistent executive format):

Executive Summary (non-technical, concise)

Incident Type with confidence level

Impact Snapshot (Operational, Financial, Regulatory/Legal, Reputation)

Top 3 Priority Actions for the next 24–72 hours

Key Questions for Leadership

Explicit assumptions (only when information is missing)

The result is a short, scannable brief designed for executives and board-level discussions.

How we built it

This project is a new application built specifically for this hackathon.

BoardBrief AI uses Gemini 3 as a reasoning engine, not as a chatbot. The system:

Receives a raw incident description

Applies a structured system prompt focused on executive decision-making

Uses Gemini 3 to reason about impact, urgency, and priorities

Produces a deterministic, board-friendly brief in a fixed format

Tech stack:

Next.js (UI + API route)

Gemini 3 API (LLM reasoning layer)

Deployed on Vercel

The architecture is intentionally simple to keep the focus on clarity, reasoning quality, and real-world usability.

Challenges we ran into

The main challenge was avoiding hallucination and overconfidence. Executive decisions require restraint, not speculation. To address this, we:

Enforced a strict output structure

Required confidence levels and explicit assumptions

Limited recommendations to realistic actions within 24–72 hours

Tuned the model temperature for consistency and reliability

Accomplishments that we’re proud of

A clean, focused demo that works end-to-end

Consistent executive output across different incident types

Clear differentiation between technical reporting and decision support

A deployable tool that can be used immediately by security and leadership teams

What we learned

We learned that the hardest part of using AI for security is not detection, but translation. Executives don’t need more alerts — they need context, priorities, and decisions. Designing AI outputs around the decision-maker fundamentally changes how security tools should be built.

What’s next

Future iterations could include:

Mapping incidents to common security frameworks (NIST, ISO)

Organization-specific risk profiles

Integration with ticketing or SOC tools

For this hackathon, the focus remains on clarity, decision support, and a strong executive brief.

Built With

• gemini-3
• google-generative-ai-api
• next.js
• typescript