Vultr

Top Builders

Explore the top contributors showcasing the highest number of app submissions within our community.

Vultr

Vultr is a leading high-performance cloud computing provider that offers a wide range of services, including scalable GPU instances specifically tailored for demanding AI and robotics workloads. Known for its global network, competitive pricing, and robust infrastructure, Vultr enables developers and businesses to deploy and manage powerful cloud resources with ease.

General
Author	Vultr LLC
Release Date	2014
Website	https://www.vultr.com/
Documentation	https://docs.vultr.com/
Technology Type	Cloud Computing Provider

Key Features

Global Network: Access to high-performance data centers worldwide for low-latency deployments.
Scalable GPU Instances: Offers powerful NVIDIA GPUs for AI, machine learning, and high-performance computing tasks.
Flexible Cloud Servers: Provides various instance types, including bare metal, cloud compute, and dedicated cloud, to suit diverse needs.
Custom ISO Support: Allows users to deploy custom operating systems or applications.
API and CLI Access: Programmatic control over all cloud resources for automation.
Managed Kubernetes: Simplified deployment and management of containerized applications.

Start Building with Vultr

Vultr provides an ideal platform for deploying AI and robotics projects that require significant computational power. With its high-performance GPU instances and global infrastructure, developers can train complex models, run simulations, and host AI-powered applications efficiently. Explore their documentation to get started with deploying your next-generation AI solutions.

👉 Vultr Documentation 👉 Vultr GPU Cloud Servers

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VULTR AI Technologies Hackathon projects

Discover innovative solutions crafted with VULTR AI Technologies, developed by our community members during our engaging hackathons.

Agent Atlas

Atlas: The Intelligence Platform That Sees Through What Your Tools Can't The surface web is a lie. Pricing pages hide true cost. Press releases obscure strategy. Reviews get filtered. Filings lag news. Credentials leak. And brand sites get cloned. Enterprise intelligence teams spend 40+ hours assembling ground-truth answers—stitching together data from 6+ tools, each with different APIs, rate limits, and blocking mechanisms. Atlas eliminates this fragmentation. Ask Atlas any business question. It autonomously decomposes the query, orchestrates 7 specialized intelligence modules in parallel, and produces a single institutional-grade brief—complete with source citations and confidence scoring. Each module is powered by Bright Data's most advanced products: Web Unlocker (bypass blocks, CAPTCHAs, JS rendering), Scraping Browser (full automation + screenshots), Web Scraper API (distributed scale), SERP API (discovery), Residential Proxies (geo-distributed), and MCP Server (orchestration layer). The 7 modules span all three tracks: - TruePrice (GTM): Completes checkout flows across geographies to reveal true pricing—taxes, fees, regional markups - Signal (GTM+Finance): Detects strategic intent from hiring patterns, exec moves, tech stack signals - Filing (Finance): Surfaces material regulatory changes with automated materiality scoring - AltData (Finance): Composite distress/momentum score from Glassdoor, G2, marketplace signals - Visual (Security): Vision AI detects brand impersonation via side-by-side lookalike comparison - Exposure (Security): Scans paste sites, GitHub, forums for credential & PII leaks - Investor (All tracks): Discovers active VC firms investing in target sectors Built on LangGraph, Pydantic , FastAPI, Claude, and deployed to Vercel + Vultr. The architecture is deliberately MCP-first—judges explicitly reward deep Bright Data integration, and Atlas makes this architectural commitment visible in every tool invocation.

Supplier Pulse

The application automates deep-dive web research and compliance profiling using the following core capabilities: Active Real-Time Scraping: Queries live web data using standard search pipelines or tunnels requests through robust Bright Data SERP/Web Scraping APIs to gather up-to-the-minute records across six key sector categories: Jobs & Hiring, Corporate News, SEC & Compliance Filings, Workplace Reviews, Official Domain Health, and Social Sentiment. Specialist Multi-Agent Pipeline: Deploying custom-modeled cognitive agents (such as the Lead Orchestrator, Financial Solvency Expert, Regulatory Counsel General, Workplace Operations Officer, Public Relations Sentinel, and Social Pulse Expert) to analyze, sanitize, and verify scraped sources under strict category filters. Cognitive Signal Classification: Dynamically processes individual research entries to extract actionable "Pulse Signals," automatically sizing positive developments and negative anomalies on a normalized severity scale. Risk Metrics & Executive Reporting: Synthesizes the cumulative vector telemetry to compute overall risk scores and compiles detailed multi-sector advisory audits ready for threat mitigation reviews.

Kraken Alpha Agent

Kraken Alpha Agent is an autonomous trading agent built for the Kraken Trading Performance track. The project focuses on xStocks strategy selection, risk-controlled execution, and transparent PnL reporting. The agent ranks xStocks candidates, runs a reproducible hackathon-window backtest, applies strict guardrails, and exposes the result through a public Vercel dashboard. The core demo shows the full workflow: signal ranking, dry-run execution, risk checks, backtest performance, and judge auditability. During the audited 13-19 May 2026 hackathon window, the backtest shows +19.18 USD PnL across 10 trades, 80% win rate, and 0.06% max drawdown. A 30-day baseline shows +33.56 USD across 138 trades with 53% win rate. Important transparency note: live xStocks execution was blocked at the Kraken venue/account level for the Cyprus EU account used in the hackathon. The project therefore reports xStocks PnL from reproducible backtests, not from live xStocks fills. A short crypto diagnostic session produced live fills outside the xStocks track, proving the engine, API key, IP setup, and execution pipeline work end-to-end. The system defaults to dry-run mode and requires triple opt-in before any live order. It also enforces 1.0x leverage, no shorting, reduce-only exits for futures, and strict rejection handling for Kraken responses. The goal is simple: make autonomous trading agents measurable, risk-aware, and auditable enough for judge verification.

HEXFIRE — Break Your Agents Before Production

The Agentic Black Box: $4.8M is the average cost of a production AI failure because enterprises deploy non-deterministic agents blind. Traditional software fails predictably, but AI agents fail probabilistically. When an agent hallucinates a variable or fails to call a tool, it confidently carries that corrupted data downstream, infecting the entire pipeline. By the time anyone notices, the damage is done. The Solution: Deterministic Chaos Inspired by Netflix’s Chaos Monkey, HEXFIRE is the world's first Chaos Engineering platform purpose-built for autonomous AI agents. We deliberately break your agent workflows to show you exactly where they crumble. Instead of guessing, HEXFIRE lets you execute targeted strikes. You can inject 6 deterministic fault scenarios into any step of your pipeline: Hallucinations, Tool Timeouts, Adversarial Prompts, Context Corruption, Latency Spikes, and Permission Revocations. Technical Gravity (Beyond the Wrapper) Remove ALL LLM calls from HEXFIRE and you still have four custom, independent computer science systems. The AI enhances HEXFIRE; it doesn't define it: DAG Cascade Analysis: Agent pipelines are Directed Acyclic Graphs (DAGs). When a fault hits one node, HEXFIRE mathematically traverses the downstream edges to determine the "blast radius." Deterministic Resilience Scoring: We compute a hard, mathematical ★-to-★★★★★ safety rating based on Survival Rate and Fault Isolation. Cryptographic Proof: Every test execution is hashed into a SHA-256 tamper-evident compliance audit chain. Generative Forensics: Gemini 2.5 Flash analyzes the wreckage and generates an exportable forensic report explaining exactly what died and how to patch it. Sponsor Integration HEXFIRE utilizes Vultr Serverless Inference for ultra-low latency execution and massive concurrency during chaos testing spikes. We leverage Google Gemini 2.5 Flash for deep resilience analysis, forensic reporting, and robust 503 capacity fallback chains. Built solo by Shree Shah.

Synapse Corp AI

Synapse AI is an enterprise-grade multi-agent workflow automation platform designed to simulate how real organizations operate using autonomous AI agents. The platform includes specialized agents such as HR, CTO, CFO, CEO, and Risk Management agents that collaborate intelligently to perform tasks like AI-driven interviews, candidate evaluation, operational analysis, workflow automation, and executive decision-making. Unlike traditional AI assistants or single-agent chatbots, Synapse AI focuses on collaborative intelligence where multiple AI agents communicate, reason, and coordinate together to solve complex organizational workflows in real time. The system supports multimodal interactions including text, documents, reports, and speech inputs, allowing users to simulate real enterprise environments and automate time-consuming operational processes. For example, users can conduct AI-powered HR interviews, upload business reports for executive analysis, or generate strategic recommendations through coordinated AI agent discussions. Technically, the platform is built using Next.js, FastAPI, Gemini AI, Speechmatics, Supabase, Docker, and Vultr cloud infrastructure. The architecture uses scalable distributed services, asynchronous processing, and modular AI orchestration to ensure reliability, low latency, and production-style deployment readiness. Synapse AI demonstrates how autonomous AI systems can function like real organizational teams, helping businesses improve operational efficiency, reduce repetitive manual work, accelerate decision-making, and create scalable intelligent enterprise workflows for the future of AI-driven organizations.

ATRIO Boardroom

**Founders and family offices decide alone.** Big calls get either delegated to a single advisor (fast, single point of failure) or convened with a committee (slow, hard to schedule, hard to audit). ATRIO Boardroom is the middle option: an AI boardroom that holds a real debate, enforces a per-tenant mandate at machine speed, and replays every decision in six months. ## Try the live demo **URL:** http://45.77.52.54:8080 (Vultr, Frankfurt) Click **Demo founder** on the sign-in screen — one click, no email — then type a boardroom question. Watch 5 specialist AI agents stream real Gemini 2.5 reasoning live, ~25 s. Go to Treasury, propose a SHV-xStock buy, try to self-second-sign (API refuses), open a new tab as **Demo CEO**, second-authorise, trade executes against Kraken paper. Download the board-pack PDF. Open the audit log. Six minutes, full lifecycle. ## The wedge - **Debate**, not consensus-on-rails. Six personas with distinct system prompts, distinct model assignments (Gemini 2.5 Flash for specialists, 2.5 Pro for Counsel), and dissent-driven turn-taking. - **Enforce**, at the API. A per-tenant `Mandate v1` (permitted instruments, daily loss limit, single-instrument max, permitted side) is the only path to a treasury action. Two-party auth cannot be bypassed by the UI. - **Audit**, by default. Every turn, vote, model call, and state transition writes to an append-only log. Exportable as JSONL + manifest. ## Why this isn't slideware - **381 / 381** backend tests pass at **90.68 %** coverage - **24 / 24** demo-video structural + **14 / 14** OCR verification - **54 / 54** pitch-deck structural + **12 / 12** OCR verification - **5 / 5** live multi-agent debate against real Gemini in ~25 s (no mocks) - **19** real bugs found and root-caused during the sprint ## Sponsors used Vultr · Google Gemini · Featherless · Speechmatics · Kraken xStocks · LiveKit. License: Apache 2.0.