Cortelligence AI
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Cortelligence is a production-grade AI Business Intelligence platform built on Python/Flask, designed to replace static chat wrappers with a "Living Strategy" system that tracks and adapts business plans over time. Key Selling Points (The "Unfair Advantage"): * Living Strategy Engine: Solves churn by allowing users to log weekly metrics (Revenue, Users). The AI analyzes progress and auto-generates course corrections, creating long-term data lock-in. * Zero-Knowledge Security: Features client-side AES-256 encryption, ensuring total data privacy (even admins cannot read user strategies), a critical feature for selling to finance/legal sectors. * Visual Intelligence: Renders native, mobile-responsive Gantt Charts, Heatmaps, and Decision Trees directly in the chat, plus professional PDF exports. Technical Specifications: * Stack: Custom Python (Flask) backend & Vanilla JS frontend (100/100 Performance). * Infrastructure: Google Firestore (NoSQL), Docker/Hugging Face ready. * Integrations: Stripe (Metered usage) and OpenRouter (Swaps between GPT-4o, Claude 3.5, Gemini 1.5 instantly). The Opportunity: A turnkey asset perfect for Marketing Agencies or Fractional Executives looking to white-label a high-value consulting tool to automate client reporting and strategy. Included in Sale: Full Source Code (GitHub), IP Rights, Infrastructure Transfer, and 30 Days of Developer Support.
Cortelligence AI GitHubCortelligence AI's answer
It transforms static AI advice into a "Living Strategy." Unlike standard wrappers that generate text once, Cortelligence creates a persistent database record for every plan, allowing users to log weekly metrics (revenue, users) and receive AI-driven course corrections based on real progress. It also features client-side Zero-Knowledge (AES-256) encryption, ensuring total data privacy suitable for enterprise use.
Cortelligence AI's answer
Most competitors are "fire-and-forget" tools that leave users with a static PDF they never look at again. Cortelligence acts as an ongoing accountability partner. It offers deeper, role-based analysis (simulating specific C-suite executives like a CFO or CMO) constrained by 50+ parameters for realism, and visualizes data with native Gantt charts and heatmaps, providing a professional consulting experience at a fraction of the cost.
Cortelligence AI's answer
The primary audience includes small business owners, solo founders, and consultants who need high-level strategic guidance but cannot afford a full-time C-suite or expensive management consulting firms. It is also designed for marketing agencies and fractional executives looking for a white-label tool to automate client reporting and strategy tracking.
Cortelligence AI's answer
I built Cortelligence as a backend architect frustrated by the "wrapper fatigue" in the AI space. I wanted to prove that LLMs could do more than just chatโthey could act as long-term strategic partners. I engineered the "Living Strategy" engine to solve the retention problem inherent in most AI tools, creating a system that learns and adapts alongside the user's business journey, rather than just answering one-off questions.
Cortelligence AI's answer
Backend: Python (Flask) for robust, scalable logic. Database: Google Firestore (NoSQL) for real-time data syncing. AI: OpenRouter integration (seamlessly swapping between GPT-4o, Claude 3.5 Sonnet, and Gemini 1.5 Pro). Security: Native AES-256 encryption libraries for client-side data protection. Frontend: Vanilla JavaScript/HTML5 for maximum performance (100/100 Lighthouse scores).
Cortelligence AI's answer
Pre-revenue asset (No current customers). Designed for Marketing Agencies. Ideal for Fractional CFOs/CMOs. Perfect for B2B SaaS Founders.
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The core of the ecosystem is the official open-source server hosted on GitHub. It is written in TypeScript and implements the full MCP specification. - Source: dev.to / 4 days ago
This is why the gate needs a trace it can trust, and why AgentLens is the other half of this workflow. agent-eval scores and gates the output; AgentLens captures the trace of how the agent got there โ every model call and tool step, the resolved inputs (not the templated ones), the raw outputs. That trace is exactly the unforgeable, agent-didn't-author substrate that Tier 1+2 need to score against. Without it,... - Source: dev.to / 5 days ago
## Tell Git to start tracking your project Git init ## Take a snapshot of all your current files Git add . ## Save this snapshot with a description Git commit -m "Initial commit from AI tool" ## Connect your local project to GitHub ## Get repository URL from your GitHub page ## it looks like https://github.com/your-name/your-repo.git Git remote add origin PASTE_YOUR_URL_HERE ## Upload your code to GitHub Git... - Source: dev.to / 14 days ago
Conclusion Next time Git insists a private repository doesn't exist, skip editing your config file and head straight to the Windows Credential Manager. Wiping out the stale git:https://github.com entry forces a clean handshake, getting you back to coding in less than a minute. - Source: dev.to / 15 days ago
Gitea is where all private repositories live: infra configs, personal projects, anything I don't want on a third-party server. Public projects still go to GitHub because that's where the audience is, but a number of those GitHub repositories are mirrored back to Gitea as a local backup. The split is simple: Gitea for control and resilience, GitHub for reach. - Source: dev.to / 16 days ago
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