Jaime Aza

Proxy interceptor for Claude Code that closes the organizational alignment gap: Claude Code is aligned with Anthropic's values, but not with the policies of each company deploying it. Tranquera is the middle layer — a silent customs checkpoint that enforces no-code rules at runtime with a Regex → Pattern → Haiku 4.5 judge cascade under 200ms of overhead and four explicit actions (BLOCK · REDACT · WARN · LOG). The (non-technical) compliance officer defines policies in natural language from a visual builder; devs onboard with a single command (`npx tranquera setup`, Google OAuth device flow and automatic export of `ANTHROPIC_BASE_URL` to the shell rc). Per-dev attribution is solved by baking the token into the URL path — Claude Code does not allow custom headers. An AI Suggestor with a daily cron and Haiku 4.5 proposes new rules from the LOGs with a human in the loop. Postgres + pgvector ready to pre-filter rules by semantic similarity. Winner of the AI Security track and the overall prize at Platanus Hack 26 Buenos Aires (main sponsor: Anthropic).

A team of financial agents you talk to via chat — from WhatsApp, Telegram, Gmail or the web. Its promise: "it knows how you live, it invests like you are." Four specialized agents coordinate: (1) Expenses & income records and classifies transactions, generates monthly summaries and detects historical patterns; (2) Investments prepares stock operations on Wallbit but never executes them without your approval; (3) Market analyst contextualizes prices, trends and asset fundamentals according to your profile; (4) Risk profile measures your real tolerance from your history (not questionnaires) and blocks incongruent operations. You log expenses the way you talk — text, audio or a photo of the receipt — and Gmail sync captures transactions without manual input; search is in natural language, with no filters or exact categories, over embeddings in pgvector. The money lives in Wallbit (not in Tresqu): from the same chat you buy and sell stocks, ETFs and bonds, transfer and check balances live, with multi-currency support (COP, USD, EUR and more) and real-time conversions.

Professional gallery delivery platform for photographers with state-of-the-art multimodal AI. It automatically analyzes every photo with GPT-4o and Gemini 2.0 Flash: assigns a 1-10 score, evaluates composition, pose and background quality, categorizes scenes (ceremony, portraits, party, outdoors...) and generates project highlights. It includes semantic photo search in natural language ('bride dancing', 'table decoration') with multimodal RAG using Google's Gemini Embedding 2 — Google's first natively multimodal model mapping text and image into the same vector space — stored in pgvector. The public gallery reorders photos based on the client's favorites and writes poetic cover phrases with AI. Complemented by festora-vision-api: an independent microservice with blur detection (Laplacian), BRISQUE/NIMA technical scoring, emotion analysis (DeepFace) and CLIP/DBSCAN semantic clustering.

End-to-end platform for beverage businesses (slushies, frappés, cocktails, bars and restaurants) with native AI at every touchpoint. The digital menu recommends drinks based on the customer's mood or preferences via GPT-4o-mini, transcribes voice commands with Whisper and shows daily AI-generated motivational phrases. The admin panel includes a professional product image generator with GPT Image 1.5 and Cloudflare R2, automatic description suggestions, per-table order management, inventory, operating expenses, analytics and a real-time multiplayer game 'Duelo Frostbyte' over WebSocket.

Real-time multiplayer typing race inspired by Monkeytype. Anyone can create a room with a 5-character code, share the link and compete for the highest WPM on the same text, with a spectator mode to join rooms mid-race. The architecture runs 100% on the edge over Cloudflare Durable Objects: one 'Room' DO per room (authoritative state, WebSockets with the Hibernation API, persistent hostToken) and a 'RoomRegistry' singleton that keeps the global list of active rooms via RPC between DOs. The clock, the text and the ranking are decided server-side, so cheating by changing the local clock is impossible. Includes 5 themes, key sounds synthesized with the Web Audio API (no samples) and a host/player/spectator model with kick and race restart.

Windows desktop app that transcribes speech to text in real time and types the result directly wherever the cursor is — no copying, no pasting. Push-to-talk with F9: hold to speak and release so the corrected final text appears in any app (VS Code, Word, Notion, Chrome…). Supports two swappable engines: Deepgram Nova-3 (cloud, low latency, simultaneous es+en bilingual with LANGUAGE=multi) or local faster-whisper (no internet, no API key, tiny→large-v3 models). Includes a Vercel-style floating HUD with timer, live preview, voice visualizer and similarity-based deduplication. Lives as a system tray icon, with VAD via silero-vad ONNX (no PyTorch). Packaged with PyInstaller + Inno Setup as a native .exe installer.

Web app that converts a 2D image into a navigable 3D point cloud using AI depth estimation. The backend (FastAPI + Docker on Railway) wraps Depth-Anything-V2 (ViT-S checkpoint) and returns the depth map as a grayscale PNG. The frontend combines the RGB image and the depth map in utils/pointCloudUtils.ts: for each pixel it generates a 3D point where X,Y map to normalized space (NDC-like, with inverted Y and height/width aspect ratio) and Z = (depth/255) × depthScale, controlled by sample rate and depth exaggeration sliders. The result is two Float32Arrays (positions + colors) rendered with React Three Fiber + drei as a THREE.Points with vertexColors. It supports three swappable depth backends: a self-hosted FastAPI server, HuggingFace Spaces or the OpenAI Images API.

Real estate semantic search engine with a RAG architecture covering more than 8,800 properties in Mexico. The user asks in natural language ('spacious house with a garden in Mérida, 3 bedrooms'), Gemini 3 Flash extracts structured filters (city, type, bedrooms, price), Qdrant pre-filters and vector search retrieves the most semantically relevant properties. It supports multimodal RAG with Google's Gemini Embedding 2: each property is represented by a single 3072-dimension vector fusing the text description with up to 6 images in the same vector space — enabling search by text or by image. It also supports swappable embeddings (OpenAI text-embedding-3 and gemini-embedding-001) with a React playground featuring an interactive similarity chart and a conversational agent with LangGraph (ReAct). Deployed on Railway + Vercel + Qdrant Cloud.