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Top Builders

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

Mistral AI

Mistral AI develops a wide spectrum of AI models and services, enabling developers, researchers, and businesses to build, deploy, and fine-tune large language and multimodal models.
The company focuses on open weights, reasoning capability, multimodality, and enterprise-grade features such as long context windows, domain-specific deployments, and fine-tuning options.

General
Founded2023 (Paris, France)
FoundersArthur Mensch, Guillaume Lample, Timothée Lacroix
Valuation~€14 billion (Series C, September 2025)
InvestorsASML (largest shareholder), Microsoft, CMA CGM, others
TypeLarge language and multimodal models

Mistral Models

Mistral divides its lineup into open models (weights freely available) and premier models (API-first, enterprise-grade).
Here are the most important families:

  • Mistral 7B – Compact, open-weight dense model for efficient deployment.
  • Mixtral 8×7B / 8×22B – Sparse mixture-of-experts models balancing performance and cost.
  • Mistral NeMo 12B – Strong open-weight model for multilingual and reasoning tasks.
  • Codestral – Code-oriented models for software engineering and developer tools.
  • Pixtral – Multimodal family supporting text + image inputs (e.g. Pixtral-12B, Pixtral Large).
  • Magistral – Reasoning-focused models; Magistral Small (open-weight) and Magistral Medium (enterprise).
  • Mistral Medium 3 / 3.1 – Premier multimodal models with ~131K context length, enterprise-grade APIs.
  • Mistral Large / Large 2 (123B) – Very large dense models with long context, available via API.
  • Specialized Models – OCR models (e.g. mistral-ocr-2503), embeddings, moderation, and speech (Voxtral).

La Plateforme

Mistral provides its own developer and enterprise platform, called La Plateforme, where you can:


Mistral AI - Boilerplates

Get started quickly with open-weight or API integrations:


Mistral AI - Tutorials

Learn how to build with Mistral’s models:


Mistral AI

Most important links to explore Mistral’s ecosystem:


Mistral AI AI technology page Hackathon projects

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

Traca

Traca

Overview traca is a split-view web platform combining live market dashboards with a conversational AI analyst. It delivers instant market intelligence through plain-language explanations of price movements and technical patterns, behavioral coaching that detects emotional trading signals like FOMO and revenge trading, and social automation via AI personas that generate platform-optimized content for LinkedIn and X. ✨ Core Features (MVP) Real-time Market Insights: Direct integration with Deriv API across Forex, Crypto, and Stock markets provides live pricing and historical data. Conversational AI: A unified chat interface handles market analysis queries, delivers behavioral feedback, and creates social media content in one seamless flow. Split-View Dashboard: Side-by-side layout presents live price charts, sentiment indicators, and AI analyst chat for efficient decision-making. Behavioral Pattern Detection: Advanced algorithms identify win/loss streaks, risk escalation patterns, and impulsive behavior, delivering timely nudges and habit-building reinforcement. Social Content Drafting: Platform-aware content generation produces professional LinkedIn posts and concise X updates tailored to each network's format. 🏗️ Architecture traca employs a Modular Monolith architecture optimized for real-time data streaming and AI inference: Frontend: React (Vite), TailwindCSS, shadcn/ui, and Zustand for state management. Backend: FastAPI (Python) with Uvicorn and WebSocket support for real-time communication. AI Engine: Mistral API cloud LLM for natural language understanding, market analysis, and content generation. Data Source: Deriv API integration for live market pricing, historical trade data, and account activity. Persistence: SQLite database stores trade history, session-based chat memory, and content drafts. This architecture ensures low-latency market data delivery, responsive AI interactions, and scalable performance.

Regulatory Radar - AI-Powered Compliance Guardian

Regulatory Radar - AI-Powered Compliance Guardian

The Problem: In the fast-paced world of fintech, marketing teams are often slowed down by a critical bottleneck: regulatory compliance. Regulations like the DFSA (Dubai Financial Services Authority) rulebook change frequently. Currently, every marketing asset requires manual legal review, a process that can take up to 3 weeks. This delay causes missed market opportunities, while human error during manual checks exposes the company to massive regulatory fines and reputational damage. The Solution: Deriv Regulatory Radar is an intelligent, automated compliance platform that bridges the gap between marketing agility and legal safety. It is not just a checker; it is a full-cycle compliance guardian powered by Google's Gemini Pro. Key Features: Dynamic Rule Extraction: Unlike static tools, our system allows legal teams to upload raw PDF regulations (e.g., a new DFSA update). The system uses AI to read the document, extract specific actionable rules, and update its database instantly. Smart Violation Detection: Marketers simply upload an image of an advertisement. The system extracts the text and checks it against thousands of active rules. It uses "Smart Trigger" logic to ensure relevance—for example, strictly applying crypto warnings only when cryptocurrency is mentioned, reducing false positives. Instant Auto-Remediation: This is our game-changer. When a violation is found (e.g., a "Guaranteed Profit" claim), the system doesn't just reject the ad. It uses Generative AI to rewrite the copy instantly, preserving the marketing punch while satisfying legal requirements. Impact: Deriv Regulatory Radar transforms compliance from a 3-week blocker into a 30-second step. It allows Deriv to scale marketing efforts aggressively without risking regulatory drift, ensuring that the brand remains both competitive and compliant.

Primuez Guard

Primuez Guard

Primuez Guard is the "Firewall" for Agentic Commerce. As AI agents begin to spend money autonomously, the risk of automated fraud increases. We built a Zero-Trust security layer that vets every transaction before it happens. The Problem: Invoice fraud and phishing are evolving. Standard wallets do not verify who you are paying, leading to lost funds. I personally lost money to a "verified-looking" phishing link, which inspired this solution. The Solution: Primuez Guard intercepts invoice data and performs a ruthless forensic investigation: Visual Analysis: Uses Mistral OCR to read the raw invoice/contract. Deep Forensics: Uses Tavily to crawl the vendor’s website and search for "scam" footprints or deep-path phishing patterns. Reasoning: Uses DeepSeek V3 and Gemini to act as a "Judge," assigning a risk score (Safe, Caution, Unsafe). Settlement: If safe, it unlocks the payment UI to execute a USDC transaction on the Arc network. Feedback on Circle Origin (Vibecoding): We utilized the Origin "vibecoding" workflow to prototype our Payment Terminal UI. Even though we encountered regional access issues with the live API, the tool's concept significantly accelerated our frontend development. It allowed us to generate a professional, dark-mode component that visually integrates with the Arc ecosystem without writing boilerplate React code. Tech Stack: AI: Google Gemini 2.5, DeepSeek V3, Mistral. Blockchain: Arc L2, Circle USDC. Orchestration: n8n. Links: Repository URL: https://github.com/Primuez/Primuez-Guard Demo URL: https://primuez-guard.vercel.app Video Demo URL: https://youtu.be/yM2_8j5PDkQ