Featherless

Top Builders

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

Featherless

Featherless is a serverless platform designed for the deployment and execution of AI models, facilitating seamless integration with the Hugging Face ecosystem. By abstracting away the complexities of infrastructure management, Featherless enables developers to focus on their applications and AI models, offering an efficient and scalable solution for various AI-related tasks.

General
Author	Featherless
Relese date	2020
Website	Featherless
Documentation	https://featherless.ai/docs/getting-started
Discord	https://discord.com/invite/7gybCMPjVA
Type	AI deployment platform

Key Features

Serverless Architecture: Eliminates the need for manual server management and supports automatic scaling.
Seamless Hugging Face Integration: Provides effortless access to a vast library of pre-trained models from Hugging Face.
Support for Multiple AI Models: Compatible with large language models (LLMs), text-to-speech, image generation, and speech-to-text applications.
API-First Approach: Designed to easily integrate AI capabilities into new or existing applications through APIs.
Cost Efficiency: Operates on a pay-as-you-go pricing model, optimizing costs by charging only for the resources used.
Scalability and Performance: Capable of automatic resource scaling to handle varying levels of demand without manual input.

Use Cases

Application Development: Incorporate AI functionalities like text analysis, image processing, and speech recognition into web and mobile apps.
Data Science and Research: Deploy pre-trained models for data analytics, machine learning research, and rapid prototyping.
Content Generation: Utilize AI for automated content creation, including text generation, voiceovers, and image synthesis.
Customer Interaction Platforms: Implement conversational agents and chatbots powered by large language models.
Accessibility Tools: Create applications that assist with real-time text-to-speech and speech-to-text conversions, enhancing accessibility.

Get Started Building with Featherless

To start building with Featherless, visit the official documentation for comprehensive guides and API references. Begin by signing up for an account, exploring available pre-trained models, and following step-by-step tutorials to deploy your first AI model in a serverless environment. With Featherless, developers can create powerful, scalable, and cost-effective AI-driven applications with ease.

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Featherless AI technology page Hackathon projects

Discover innovative solutions crafted with Featherless AI technology page, developed by our community members during our engaging hackathons.

Jaga — Cough-Based TB Triage

In 2024, around 2.4 million people who developed tuberculosis went uncounted—undiagnosed or unreported (WHO Global Tuberculosis Report 2025). Jaga, built by team Singkong, is an investigational phone-first triage prototype that helps close that gap. A community health worker records one guided cough and enters supported clinical inputs; Jaga returns a follow-up urgency estimate so programmes can prioritize who to send for confirmatory TB testing first. No X-ray machine, lab, or radiologist required. Two independent, never-fused AI pathways drive it. Gema handles cough plus clinical data: a Rust YAMNet gate confirms the audio is a cough, a local WavLM Large model embeds it entirely on-device, and XGBoost combines that with demographics. Prisma is a separate digital chest X-ray path (DenseNet121 + CLAHE) with its own estimate and a Grad-CAM heatmap. AMD is load-bearing: both models were trained on AMD Instinct MI300X via AMD Developer Cloud (ROCm PyTorch), and all model inference runs locally in Rust and Python. Fireworks serves only the Gemma guidance chat. Jaga does not diagnose or rule out TB. Every symptomatic person is directed to confirmatory testing—the estimate only prioritizes urgency.

MangomicAI

The Problem: Creating a visual novel or comic requires massive effort in storyboarding, maintaining character consistency, and managing hundreds of high-res image assets. The Solution: Genblaze Visual Novel Studio pairs you with an AI Art Director. You simply chat about your story idea in plain English. The AI extracts a structured script, casts characters, and automatically orchestrates the generation of an entire visual storyboard. How I built it (Architecture): Interactive Frontend: A stunning, glassmorphism UI built with Next.js and Framer Motion, utilizing Server-Sent Events (SSE) to stream generation progress to the user in real-time. AMD Compute (The Engine): We deployed a custom ComfyUI inference server on a powerful AMD MI300X droplet. Our Python backend dynamically compiles complex ComfyUI workflows (utilizing Animagine-XL) and sends them to the AMD node for blazing-fast image generation. Backblaze B2 (The Vault): As soon as the AMD droplet finishes rendering a panel, our FastAPI backend streams the raw bytes directly into a Backblaze B2 bucket. The assets are then served instantly back to the frontend via B2's high-performance public CDN. This architecture proves that complex, multi-modal AI workflows can be orchestrated seamlessly by combining AMD's cutting-edge accelerators for heavy compute with Backblaze B2 for reliable, cost-effective asset delivery.

THE COUNCIL: Expert Advisors Who Fight For You

Everyone faces life-changing decisions alone. THE COUNCIL changes that by giving you your own personal advisory board. Submit your query—whether it's a high-stakes startup offer, career transition, or relocation—and watch five autonomous AI agents with distinct, persistent personalities deliberate in a live-streamed debate. Under the hood, THE COUNCIL is a multi-agent system built on Band.ai. Instead of a single LLM wearing five prompts, we deploy genuine model diversity: Qwen 2.5-32B (The Skeptic) analyzes risks, Llama-3.1-70B (The Strategist) identifies long-term growth, DeepSeek-R1-70B (The Numbers) quantifies quantitative metrics, Llama-3.1-8B (The Devil's Advocate) stress-tests consensus, and GPT-4o-mini (The Chair) synthesizes the room. The debate orchestration runs sequentially via FastAPI WebSockets to stream arguments as they are generated. Unlike typical chatbot wrappers, THE COUNCIL features heavy engineering depth: 1. Deterministic Stakes Classifier: Scores severity (1-10) and risk factors (cliff, vesting, relocation) deterministically without AI. 2. Live Market Grounding: Career queries trigger Brightdata web scraping to search salary listings, providing real-world benchmarks to 'The Numbers'. 3. Convergence Calculator: A custom algorithm that measures consensus (0.0-1.0) using position agreement and semantic text similarity. 4. Cryptographic 'Stare Decisis': Inspired by judicial tradition, it extracts minority dissents and SHA-256 hashes them directly into an immutable verdict chain. 5. 6-Table Database Persistence: Complete deliberation history mapping decisions, arguments, verdicts, evidence, and dissents in SQLite. Presented in an Apple-inspired editorial Next.js UI using stark light-mode whitespace, Playfair Display serif typography, and elegant card components with smooth micro-animations, the system feels alive, premium, and authoritative. Deliberation, not just generation.

AegisOne

AegisOne XDR is an enterprise-grade multi-agent cybersecurity platform that autonomously detects, investigates, explains, and responds to security incidents using Band, Featherless, MCP servers, RAG, and multimodal analysis. Features Multi-agent architecture powered by Band Multimodal threat analysis RAG-based cybersecurity knowledge retrieval Human-in-the-loop approval workflow Autonomous remediation and verification Explainable AI with complete audit trails MCP Integrations VirusTotal AbuseIPDB Shodan GitHub Slack Email Filesystem Vision Build an explainable AI security operations team where specialized agents collaborate through Band to detect, investigate, and respond to cyber threats while keeping humans in control.

Coder – AI Software Engineering Team

Coder is a mobile-first and desktop-capable AI software engineering platform designed to function as a complete AI development team rather than a traditional chatbot. Instead of relying on a single AI model, Coder uses four specialized agents working together through Band.ai's multi-agent collaboration system. The Planner Agent analyzes user requirements and creates a structured development plan. The Engineer Agent generates project architecture, files, and implementation code. The Reviewer Agent performs syntax validation, dependency verification, import checking, and build-readiness analysis. The Verifier Agent performs UI/UX review, functionality validation, requirement matching, and final quality assurance before delivery. Coder combines these agents inside a unified IDE experience built with Flutter. Users can open projects, browse files, edit code, preview applications, connect GitHub repositories, and export completed projects from a single workspace. The platform supports modern web development technologies including HTML, CSS, JavaScript, React, Tailwind CSS, TypeScript, Node.js, Flutter, and related frontend technologies. Unlike standard AI coding assistants, Coder introduces a configurable three-step verification pipeline that allows generated code to pass through multiple validation stages before being accepted. Users can enable or disable verification directly from the settings panel depending on their workflow requirements. Band.ai serves as the collaboration and orchestration layer, allowing all agents to communicate through shared rooms and agent-to-agent messaging. AIMLAPI and Featherless AI provide access to multiple large language models, enabling flexible model selection and cost-efficient execution. Markdown-based technical knowledge resources can be attached to agents to provide framework-specific guidance and coding standards.

PARLEY AI Orbital Negotiation System

PARLEY is a multi-agent orbital conjunction negotiation system built for the Band of Agents Hackathon 2026. It automates one of the most consequential decisions in space operations — who maneuvers, when, and by how much — without human intervention. The system runs six autonomous agents, each with a single responsibility: Sentinel monitors conjunction data and fires the first alert when collision probability crosses the safety threshold. Oracle enriches that alert with orbital parameters — fuel reserves, delta-V capacity, approach geometry — and recommends which satellite should maneuver. Operator Alpha and Operator Bravo represent each satellite operator. They negotiate directly, proposing burns, countering, and converging on a maneuver plan. Arbiter, running on an independent model, validates the agreed plan against coordination norms and issues the final verdict. Archivist seals every event into a hash-chained, tamper-proof audit trail — nothing can be altered after the fact. In a live test run, Sentinel flagged a critical conjunction between STARLINK-4412 and ONEWEB-2201 with a collision probability of 0.00018 (nearly double the 0.0001 threshold) and a miss distance of 42.3 meters. Oracle recommended ONEWEB-2201 as the maneuvering party based on its higher fuel reserves and delta-V capability. The operators negotiated and agreed on a 0.38 m/s retrograde burn, achieving a 500-meter miss distance and cutting collision probability by over 99%, to 1.4×10⁻⁶. Arbiter certified the plan, and Archivist sealed the full sequence into an immutable audit trail. PARLEY runs on Claude Sonnet 4.6 via the AI/ML API, with Featherless AI powering the independent Arbiter model, orchestrated through Band.ai's agent SDK. Every agent call is real, logged, and traceable. From detection to certified resolution — autonomously, in under a minute.