Gemini 3 Flash

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Gemini 3 Flash

Gemini 3 Flash is a highly efficient and speed-optimized multimodal AI model developed by Google DeepMind. As part of the next generation of Gemini models, Flash is designed to excel in agentic tasks, offering advanced reasoning and thinking capabilities with a focus on high throughput and low latency. This model is ideal for applications requiring rapid responses and complex processing across various data modalities.

General
Author	Google DeepMind
Release Date	2025
Website	https://deepmind.google/
Documentation	https://ai.google.dev/gemini-api/docs/gemini-3
Technology Type	LLM

Key Features

Speed-Optimized: Engineered for fast inference, making it suitable for real-time applications and high-volume workloads.
Multimodal Capabilities: Processes and understands information from various modalities, including text, images, and potentially audio/video.
Advanced Reasoning: Supports sophisticated reasoning and problem-solving for complex agentic tasks.
Agentic Workflows: Designed to power autonomous AI agents, enabling them to plan, act, and interact intelligently.
Scalable Performance: Balances high performance with resource efficiency for broad deployment.

Start Building with Gemini 3 Flash

Gemini 3 Flash provides developers with a powerful, speed-optimized model for building responsive and intelligent AI applications, especially those focused on agentic workflows. Its multimodal capabilities and advanced reasoning make it a versatile tool for integrating cutting-edge AI into products and services. Explore the developer guide to harness the full potential of Gemini 3 Flash.

👉 Gemini 3 Developer Guide 👉 Google DeepMind Research

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Google Gemini 3 Flash AI technology Hackathon projects

Discover innovative solutions crafted with Google Gemini 3 Flash AI technology, developed by our community members during our engaging hackathons.

NarrativeAegis: AI Search Visibility Platform

NarrativeAegis™ is an enterprise-grade AI Search Visibility (AISO) and reputation protection platform built for the generative search era. As search engines transition from lists of links to answering queries directly via generative AI summaries (like Google AI Overviews), brands lose visibility and control over their public narrative. NarrativeAegis solves this by providing a comprehensive auditing, benchmarking, and corrective action suite. Using Bright Data's high-performance SERP API, the platform bypasses geo-restrictions to execute multi-market, multi-lingual searches across informational, comparative, and transactional user intents. It extracts raw AI Overview contents, organic results, and citations in parallel. The cognitive layer, powered by Google Gemini 3.1 Flash, analyzes text blocks to compute exact sentiment scores, extract core claims, and evaluate competitor presence. These metrics feed into the proprietary AI Visibility Score (AVS) index, which weights presence rate, sentiment, share of voice, and geographic parity. Crucially, the platform maps cited websites to identify 'Poison Sources'—negative, outdated, or competitor-biased content influencing the AI's response. It ranks these sources using an impact vs. fixability framework and generates a step-by-step Corrective Action Playbook, giving PR and SEO teams clear, actionable strategies to reclaim their brand narrative. NarrativeAegis is wrapped in a premium, glassmorphic dashboard built using Next.js 15, custom HSL styling, and GSAP micro-animations. It operates with a zero-database footprint, utilizing React Context and LocalStorage to synchronize search history dynamically, ensuring high speed, maximum privacy, and seamless local evaluation.

BelliniGuard — AI Visitor Security Agent

BelliniGuard is an AI-powered security agent designed for residential complexes that transforms manual visitor logbooks into an intelligent, automated access control system. The agent captures visitor ID documents via webcam, extracts data through OCR, and instantly cross-references identity information against public web sources using Bright Data's Web Unlocker and SERP API — retrieving real names, verifying vehicle plate registrations, and flagging risk patterns without manual intervention. Key capabilities include: real-time identity verification by national ID number using live public web data, vehicle access control with plate + color + owner matching, a complete visitor history log per person and per apartment unit, two-factor authentication combining biometric terminals (Hikvision face/fingerprint) with AI validation, automatic pre-fill for returning visitors to accelerate entry, and a risk alert engine that detects anomalies like multiple department visits, mismatched identity documents, or vehicles with inconsistent ownership. Built with FastAPI, PostgreSQL, and Next.js, BelliniGuard integrates with Bright Data MCP Server for live web queries, Hikvision/Dahua CCTV infrastructure via API, and n8n for automated alerts and workflows. The system connects the security booth and lobby in real time, enabling coordinated access decisions across entry points. BelliniGuard addresses a real gap in Latin American residential security: buildings with sophisticated camera infrastructure but paper-based visitor registration. This project was built during the Web Data UNLOCKED Hackathon using Bright Data as the core intelligence layer for identity and vehicle verification.

Echo MultiAgent

ECHO is an autonomous multi-agent meeting workflow agent built for enterprise teams. The problem it solves: knowledge workers waste 5+ hours per week on post-meeting admin — updating CRMs, creating tasks, drafting follow-up emails, posting team summaries. ECHO compresses that to zero. HOW IT WORKS A Recall.ai bot auto-joins any Zoom, Google Meet, or Microsoft Teams call via URL — no app install, no calendar permission required. After the meeting ends, five specialist AI agents fire in sequence: 1. Action Extractor (Featherless / Llama 3.1) Extracts every commitment, deadline, and task from the diarized transcript using a domain-specialized open-source model running on Featherless serverless inference. 2. Stakeholder Classifier (Featherless / Llama 3.1) Identifies who said what, their role, company, and who owns each action item. Depends entirely on Speechmatics speaker diarization to know which speaker is which. 3. Decision Maker (Gemini 2.5 Flash) Synthesizes a full cross-system workflow: what to update in HubSpot, what to create in Linear, what to post in Slack, and what to draft in Gmail — based on all prior agent output. 4. Comms Drafter (Gemini 2.5 Flash) Writes the actual follow-up emails and Slack summaries in natural language, ready for human review or auto-send. 5. Executor Fires real API calls to HubSpot, Linear, Slack, and Gmail. Nothing is mocked. Every integration is live and auditable.

RelAI

RelAI is a messaging-first multi-agent networking platform built for AI Agent Olympics at Milan AI Week 2026. Instead of asking attendees to search directories or awkwardly approach strangers, RelAI assigns each person an AI representative that works on their behalf throughout the event. The experience starts in Telegram, where users answer a short onboarding flow about their role, interests, who they want to meet, and when they are available. Google Gemini transforms these answers into a structured networking profile and launches a coordinated agent workflow: scanning the attendee roster, ranking the strongest mutual fits, simulating short agent-to-agent conversations to test alignment and interest, finding overlapping availability, and proposing up to three high-quality meetings with clear reasons and suggested talking points. This is not a generic chatbot. RelAI implements a collaborative multi-agent system with distinct steps—profile extraction, matchmaking, representative dialogue, scheduling, and summarization—connected through a shared database and orchestrator. Users retain full control: every proposed match requires explicit approve or reject in Telegram before anything is confirmed. For organizers, judges, and power users, Mission Control is a web dashboard that visualizes the workflow in real time: a live graph of scanning, contacting, and negotiating states, an activity feed, and match cards with scores and transcripts. The stack is Next.js, Supabase Postgres, Gemini Flash and Pro, and deployment on Vultr, aligned with hackathon partners and tracks including Collaborative Systems, Agentic Workflows, Enterprise Utility, and Intelligent Reasoning. Enterprise use cases extend beyond conferences to sales roundtables, investor-founder matching, and internal offsites where quality introductions matter more than volume. RelAI demonstrates how autonomous agents can collaborate at scale while keeping humans firmly in the loop.

OmniClaims Adjuster

OmniClaims Adjuster: El Futuro de la Liquidación de Siniestros En la actualidad, el procesamiento de reclamos de seguros es un proceso manual, lento y propenso a errores. OmniClaims Adjuster revoluciona el sector Insurtech mediante una arquitectura multi-agente totalmente autónoma construida sobre la familia de modelos Gemini 3.1 de Google. Diseñado para la AI Agent Olympics Hackathon, este sistema actúa como un ajustador de seguros experto. En lugar de depender de un solo modelo monolítico, el flujo de trabajo orquesta múltiples agentes especializados trabajando en paralelo y en tiempo real: 1. Agente de Extracción: Transforma las narrativas no estructuradas del cliente en datos estructurados estandarizados bajo esquemas estrictos de Pydantic. 2. Agente de Pólizas: Analiza los términos contractuales (PDFs) verificando límites, deducibles, exclusiones y coberturas con precisión milimétrica. 3. Agente de Visión (Daños): Aprovecha la multimodalidad nativa de Gemini 3.1 Pro para examinar fotografías de evidencias, evaluando la severidad y la congruencia del daño reportado. 4. Agente Antifraude: Detecta anomalías cruzando variables (ej. inconsistencias entre la historia del cliente y la evidencia visual) para emitir una puntuación de riesgo. 5. Agente Orquestador: Consolida todos los análisis en una decisión final holística (Aprobado, Rechazado o Revisión Manual). A nivel técnico, la plataforma cuenta con un backend en FastAPI y una interfaz Gradio con diseño premium glassmorphism. Priorizando la explicabilidad (AI Transparency), el sistema expone en la UI todo el Chain of Thought (Razonamiento) de los agentes. OmniClaims Adjuster no reemplaza al ajustador humano; lo empodera resolviendo automáticamente el 80% de los casos claros y entregando un dossier procesado de alta inteligencia para los reclamos complejos.

DemoMaster

DemoMaster turns a repository or live demo URL into a polished narrated pitch video. It runs an agent workflow that understands the product, captures real browser evidence, writes a demo-led script, generates voice narration, and exports a final video with transcript and agent logs. In this demo, DemoMaster starts from a Sauce Demo URL, shows the agent run in progress, produces the pitch workspace, and plays the generated result video with real product footage. DemoMaster uses a Next.js web app with Playwright for real browser capture and video evidence. Gemini powers product understanding, pitch writing, capture-aligned narration, and voice generation. Featherless is used as an open-model critic for pitch quality checks, while Speechmatics verifies the generated narration against the transcript. The final video is rendered in-browser with canvas/WebM, then converted to MP4 with FFmpeg for submission.