Guru Meditation is an independent software studio. We design and ship multi-tenant SaaS platforms, trading systems, and the systems-level backends most teams won't touch — from the database schema to the screen.
[1] the name is a 1980s Amiga crash screen. it's a joke. the uptime isn't.
Software Failure. Press left mouse button to continue.
Guru Meditation #DEADBEEF.0000C0DE · (you won't need to)
We work end to end — architecture, backend, data, and the interface — and we stay until it's in production and staying up.
Multi-tenant products from schema to shipped UI — dozens of modules, role-based dashboards, and AI woven through the workflow, not bolted on.
Autonomous strategy engines, market-data pipelines, backtesting, and risk & position-sizing logic that holds up out of sample.
Whitelabel brokers in full: FIX liquidity aggregation, quote markup, A/B-book routing, dealing desk, exposure and margin.
Cross-platform desktop and mobile clients sharing one typed core — the same book, quotes, and order flow everywhere.
A few of the systems that came out of the studio. More land here as they ship.
Run an entire company on one system — finance, CRM & sales, supply chain, manufacturing, HR and compliance. ~80 mounted apps, 16 role-based dashboards, and roughly 1,900 modal flows, with AI threaded through search, marketing, recommendations and chat.
visit response365.ai ↗Not a rule-based bot. A meta-controller that learns across price, volume, volatility, chart patterns, market regimes, intermarket and macro signals — and sizes every position by volatility and edge. Every strategy ships only after walk-forward, out-of-sample validation.
visit piggytrader.cc ↗A broker in a box. FIX 4.4 liquidity aggregation across multiple LPs, per-group quote markup, A-book / B-book routing, an internal price-time matching engine, a dealing desk, live net-exposure tracking, auto-hedging, and a margin engine with stop-out — multi-tenant and row-level isolated.
Native desktop and mobile trading terminals built on a shared TypeScript core — the same order book, quotes and execution flow on the desk and in your pocket, wired straight into the broker backend.
Pulls stories from PDF newspapers & magazines, websites and RSS feeds, and social platforms (X, Facebook, Instagram, LinkedIn) — then segments, embeds and semantically clusters related coverage across languages, generates synopses, and ranks it all into a personalised feed. PostgreSQL for records, a Milvus vector database for semantic search, and anti-detection scraping throughout. Every LLM step — text understanding and on-page image recognition, reading and comprehension alike — runs on a local Gemma 4 model on the server, so no content ever leaves the box.
New projects land here as they ship. There are more in the pipeline — and one of them might be yours.
Tell us what you're building — or what's keeping you up at night. We read everything and reply ourselves.