Complete

Top Builders

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

Complete

Complete is an AI-powered collaboration platform designed to transform isolated AI chats into collaborative environments. It enables teams to work together with AI agents in shared, contextual workspaces, ensuring a single source of truth for conversations, context, and outputs. By integrating multiple AI models and specialized agents, Complete empowers teams to work smarter and faster through unified AI teamwork.

General
Author	Complete
Release Date	2024
Website	https://complete.dev/
Documentation	https://docs.complete.dev/
Technology Type	AI Collaboration Platform

Key Features

Collaborative AI Workspaces: Shared chat threads where teams can build on each other's prompts and maintain context across projects.
Multi-Model Integration: Run leading AI models in parallel, allowing teams to choose the best model for specific tasks like coding, reasoning, or creative writing.
Specialized AI Agents: Access role-specific agents for Product Managers, Project Managers, and Developers to automate summaries, monitor progress, and accelerate debugging.
Shared Context through Files: Organize and access documents across projects, providing AI agents with the necessary context to perform accurately.
Built-in Code Editor: An integrated environment for real-time collaboration between human developers and AI agents on codebases.
Governance and Control: Advanced tools for managing AI context, memory, and rules to ensure safe, consistent, and compliant AI usage across the organization.

Start Building with Complete

Complete offers a scalable environment for teams to integrate AI into their daily workflows. From simple shared chats to complex agentic processes, it provides the infrastructure needed for collaborative AI development and operations. Developers can leverage Complete's specialized agents and model flexibility to build more robust AI-powered applications.

Complete Resources

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complete AI technology page Hackathon projects

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

SpecForge

SpecForge is a self-assembling AI product engine that transforms a single sentence into a full, shippable product package in under 5 minutes. Built entirely within Complete.dev, it demonstrates what's possible when specialized AI agents don't just assist — they collaborate, hand off, and build on each other's work autonomously. How it works: Six purpose-built agents operate as a coordinated team across a dynamic DAG pipeline. The Orchestrator reads the incoming idea, constructs an execution graph, and sequences the agents based on what's missing from the spec. Each agent picks up where the last left off: Strategist → PRD, personas, user stories, acceptance criteria Architect → ADRs, system design, tech stack decisions Engineer → task breakdowns, code scaffolding, implementation plan Copywriter → GTM strategy, pitch narrative, landing page copy QA Sentinel → test plans, edge cases, quality gates Orchestrator → routes, sequences, validates, and self-heals on failure The pipeline is fault-tolerant: if any agent output fails validation, the Orchestrator re-invokes with targeted correction context rather than restarting from scratch. The proof is in the submission itself. SpecForge was built using SpecForge. The PRD, architecture decisions, GTM strategy, pitch deck, and implementation plan in this submission were all generated by the agents during development. This isn't a demo of what the product could do — it's evidence of what it already did. Built on: Next.js · TypeScript · Complete.dev Agent Builder · GitHub Actions · Vercel Target users: Hackathon builders, solo founders, and product teams who need to move from idea to structured execution without the overhead of a full product team. SpecForge doesn't just generate documents. It assembles the thinking.

Launchium

Launchium is a multi-agent AI platform that takes a raw startup idea and delivers a fully launch-ready startup package — in hours, not months. Most founders stall at execution. They have the idea but lack the technical team, budget, or time to validate, build, and launch. Launchium eliminates that gap. Powered by 8 specialized AI agents orchestrated via LangGraph StateGraph, Launchium autonomously runs a complete startup pipeline: it validates your idea against real market data, designs your product architecture, generates a full-stack MVP codebase, audits it for security vulnerabilities, crafts your landing page copy, builds your go-to-market strategy, optimizes for SEO, and packages everything into a downloadable ZIP — ready to deploy. Each agent operates with a reflect-and-refine loop, ensuring outputs are deep, actionable, and production-quality — not generic summaries. The entire pipeline runs in parallel, with real-time progress tracking so founders see results as they're generated. Built on Complete.dev's Agent Builder infrastructure and deployed live, Launchium is not a demo — it's a working product. Founders sign in, enter their idea, and walk away with a validated business concept, working code, security report, pitch deck, and marketing kit. No team required. No months of planning. Just launch.

Sherlock Analyzer - AI That Checks Explanations

Sherlock Analyzer demonstrates how coordinated AI agents can perform structured reasoning instead of simple text generation. Traditional chatbots provide persuasive explanations but do not show how conclusions were reached. Our system breaks reasoning into a controlled pipeline of specialized agents. A question-framing agent defines the investigation scope. A timeline agent constructs a sequence of verified events from primary sources. A claims-analysis agent compares public statements with documented actions. Finally, a synthesis agent produces a concise explanation and assigns a confidence level. The output clearly shows: • what was publicly claimed • what actually happened • where contradictions occur • how confident the conclusion is The demo analyzes the Volkswagen Dieselgate case and automatically detects conflicts between official corporate statements and regulatory evidence. Potential users include investigative journalists, compliance teams, auditors, regulators, and policy researchers who require transparent, auditable AI reasoning.

GameForge AI

GameForge AI reimagines game development by putting the power of creation in anyone's hands. Describe your game idea in plain English and four specialized AI agents will instantly collaborate to bring it to life. The Concept Architect designs the game mechanics, the Pixel Weaver defines the visual style, the Code Conjurer writes the full HTML5 game code, and the Bug Slayer polishes it to a playable state. No coding skills required. No game engine expertise needed. Just your imagination. Built on Groq with Llama 3.3 70B and Gemini as fallback, GameForge AI delivers a fully playable browser game rendered live in under 60 seconds. Users can remix their game with a single sentence, download the HTML file, or go fullscreen from a sleek cyberpunk Next.js interface. GameForge AI democratizes game creation for indie creators, educators, and storytellers, making "I have a game idea" the only prerequisite to playing it.

Prism - From Chats to Structured Product Work

Modern product teams constantly discuss bugs, features, ideas, and feedback inside chat platforms like WhatsApp, Slack, Discord, and internal threads. However, these high-value product signals get buried in noise, making manual triage slow, repetitive, and error-prone. Prism is a production-minded AI Product Signal Agent built on Complete.dev that continuously ingests messy team conversations and transforms them into structured, actionable outputs. Instead of simple summarization, Prism uses a product knowledge base and contextual understanding of the codebase to intelligently classify messages into Issues, Features, Ideas, and Marketing signals while filtering irrelevant chatter. The system orchestrates multiple AI agents in sequence: a classifier agent detects relevance and priority, an interpreter agent structures requirements and acceptance criteria, and a planning agent generates execution-ready artifacts like implementation plans, testing checklists, and documentation. A human-in-the-loop checkpoint ensures quality and control before final outputs. During the hackathon, we built a fully working pipeline that supports multi-format chat ingestion (Discord exports, text, and structured logs), real-time signal classification, a workspace board for structured triage, and an issue builder that converts raw conversations into downloadable technical plans. Prism’s core innovation is context-aware signal intelligence — it doesn’t just read messages, it understands them in relation to the product itself. The long-term vision is to integrate live WhatsApp, Slack, and Discord bots that act as always-on product observers, ensuring no critical signal is ever lost in chat history again.

CLOSET OS

CLOSET.OS is an AI-powered wardrobe operating system that turns a user’s closet into a smart, sustainable styling assistant. Users upload photos of garments once; five collaborating AI agents then tag items (Garment Vision), fetch weather and calendar context (Weather & Calendar), generate daily outfit recommendations (Stylist), identify wardrobe gaps with shopping suggestions (Gap Analyst), and track usage for sustainability insights (Sustainability). A FastAPI orchestrator and PostgreSQL backend coordinate agent calls and persist the wardrobe, while a React Native mobile app (Natively.dev) provides a polished user experience. Built entirely inside a single Complete.dev workspace, CLOSET.OS demonstrates an end-to-end, production-minded flow—agents, API, mobile app, and go-to-market assets (website, pitch deck, PR). The product reduces overbuying, increases outfit variety, and creates revenue through a freemium subscription and affiliate shopping links. Ideal for fashion-conscious, sustainability-minded users, CLOSET.OS showcases practical multi-agent collaboration solving a real-world problem with measurable environmental and commercial impact. Built entirely in Complete.dev—from system architecture to mobile app to marketing website and pitch deck—CLOSET.OS demonstrates true end-to-end, multi-agent product execution. It is not just a demo, but a scalable AI application designed for real users, real workflows, and real business potential.