Inspiration
The idea for Causarix was born from observing how my father managed three hotels in India. I noticed he was dealing with a huge number of variables every day in order to keep his operations running smoothly. I saw that his productivity was limited by the amount of time he spent reviewing and reconciling documents in order to understand his operations. And I saw how his time could be better spent innovating and improving his services. My observations led me to create a prototype of a data connector application capable of aggregating and reconciling hotel related data. However, I also realized that such a tool would only address part of a bigger problem. I saw the opportunity to create something truly innovative: A predictive tool capable of analyzing an operator’s current state and recommending adjustments for continuous improvement in their operations. This eventually led me to develop Causarix through three core phases:
- Building a data connector app for reconciling hotel operational data.
- Adding machine learning capabilities for forecasting demand and predicting outcomes.
- Finally building upon the latest developments in generative AI to create a novel approach that allows operators to reason through files using an immersive 3D Corporate Memory paired with an AI C-Suite_ that allows for an unprecedented level of interaction with company data. ## What it does Causarix is a revolutionary 3D business document reasoner that turns unstructured business documents into connected, actionable executive intelligence. It offers a suite of powerful tools for hotel and enterprise operators including:
- 3D Executive Memory Graph: A 3D knowledge graph that automatically indexes complex operational data.
- 10-Agent AI C-Suite: An immersive boardroom of 10 specialized AI executives that can reason through documents and data to advise operators and negotiate trade-offs.
- Machine Learning & Causal Simulation: Forecasting and predictive capabilities using Judea Pearl's Structural Causal Models (SCM), Box-Muller Gaussian transforms, Geometric Brownian Motion, and 95% Value at Risk (VaR) with zero arithmetic drift.
- Zero-Hallucination Grounding: Every insight and recommendation from the AI is grounded in line-level evidence from underlying source documents.
- Production Monetization: Includes LemonSqueezy Merchant checkout for Pro ($29/mo) and Enterprise Max ($39/mo) tier upgrades with real money refund capabilities. ## How we built it Causarix is an enterprise-class web application built with a variety of modern tools including:
- Frontend: Next.js 14/15 App Router, React, TailwindCSS, Three.js / WebGL
- Database & Backend: Neon PostgreSQL + Prisma ORM + Supabase dual storage
- AI/ML: Google Gemini API + Groq Llama 3 for 10-agent C-Suite modeling, retrieval, and forecasting
- Authentication & Analytics: Firebase Authentication
- Monetization: LemonSqueezy Merchant of Record API with webhook HMAC SHA256 security ```bash # Clone and run Causarix locally git clone https://github.com/novaecosystems-cloud/Synaps.git npm install npm run dev Challenges we ran into Some of the challenges we faced while building Causarix included:
Getting the 10-agent C-Suite to perform complex financial and operational analysis of hotel records without blowing through API credits. Enforcing a strict zero-hallucination policy where every single insight from the AI is backed by line-level evidence from source documents. Making enterprise-grade tools such as machine learning and predictive analytics accessible to everyday operators. Accomplishments we're proud of We are proud to have taken our prototype application and turned it into a fully fledged SaaS application used by operators across different industries. We are thrilled to see how operators engage with and benefit from our product. We are especially proud of the following accomplishments:
Turning a real-world problem we encountered on a daily basis into a successful SaaS product. Actually shipping a production-grade application live on Vercel: https://causarix.vercel.app Getting the real-time room-scale 3D graph to render smoothly in conjunction with the 10-agent C-Suite. Achieving 100% mathematical grounding in our insights with interactive line-level highlighting. What we learned I learned how to turn my initial idea for a simple utility tool into a prototype that evolved into a full-blown predictive analytics system and then finally into a multi-agent generative AI platform. I also learned a lot about the development stack including 3D WebGL graph visualization and SaaS monetization tools and tactics.
What's next for Causarix Physical Black Box for Enterprises: Developing an air-gapped, on-premises hardware appliance ("The Causarix Black Box") allowing enterprises to run 10-agent deliberations and document reasoning 100% locally with zero cloud data leakage. Expanded Industry ML Models: Adding more tools specific to the hospitality sector such as dynamic room pricing and inventory management. Voice Synthesis: Introducing voice synthesis to allow the 10-agent C-Suite to voice their opinions in live boardroom discussions. Native Ecosystem Connectors: Introducing automated connectors for PMS, Google Drive, WhatsApp, and enterprise ERPs.
Built With
- artificial-intelligence
- firebase
- google-gemini
- groq
- lemonsqueezy
- machine-learning
- next.js
- postgresql
- prisma
- react
- supabase
- tailwind-css
- three.js
- typescript
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