# How to Vibe Code Your Own TextCortex (and Stop Paying for It)

> Enterprise AI Infrastructure That Delivers ROI

- Site: https://textcortex.com
- Category: AI Infrastructure & Workflow Automation
- Verdict: **Solid side project** (68/100 vibecodeable)
- Estimated effort: 2-4 weeks part-time

## Verdict

You can build a fully functional personal clone of the core ZenoChat, RAG pipeline, and model-routing dashboard, but the 30,000-site browser extension injection engine requires significant engineering discipline.

TextCortex combines standard LLM wrappers with a complex document RAG backend and a massive browser extension toolbar. Vibecoding tools can spin up the Next.js dashboard, vector database, and chat interface in days. However, building a reliable browser extension that injects custom UI into arbitrary third-party web apps while managing cross-origin messaging, content security policies, and DOM mutation updates will test your patience with debugging asynchronous race conditions.

### What you can't replicate

- Enterprise SOC 2 and ISO 27001 security compliance posture
- Active user base of 2.4 million professionals and established enterprise brand trust
- Proprietary enterprise workflow integration templates and sales playbooks

## What it does

Enterprise-focused AI infrastructure and workflow automation platform featuring custom AI agents, knowledge management, multi-model orchestration, and a cross-platform browser extension.

### Core features

- ZenoChat conversational interface with multi-model routing
- Knowledge Bases (RAG) with document parsing and vector search
- Visual Agent Builder for task-specific AI agents
- Browser extension for contextual text injection and toolbars
- Workflow automation engine with multi-step node configuration
- Model-agnostic hub supporting OpenAI, Claude, and Gemini

## The business

### Pricing

- FREE: $0 / month
- PREMIUM: $29.99 / user/month
- ENTERPRISE: Custom

### Funding

$1.2M raised.
- Pre-Seed / Seed Round ($1.2M, June 21, 2022)
Investors: Speedinvest, Entrepreneur First, b2venture, Amar Shah, Holger Hengstler

Founded 2021.
Team size: 11 to 50 employees.

## The hard parts

- Browser extension mutation engine that safely injects floating toolbars across 30,000+ third-party web apps without triggering CSP violations
- Enterprise-grade document chunking and vector synchronization for diverse file formats
- Multi-model orchestration layer managing unified billing, context window limits, and rate limiting across disparate providers
- Strict data privacy and GDPR-compliant EU infrastructure isolation

## How to vibe code TextCortex

### Prerequisites

- Node.js (free): Required runtime for running the Next.js web application and building the browser extension bundle.
- GitHub (free): Code repository hosting and CI/CD deployment pipelines.
- Anthropic / OpenAI API Keys (Pay-as-you-go): Provides foundation models (Claude and GPT) for ZenoChat and the agent execution engine.

### Recommended AI tools

- Claude Code: Handles end-to-end multi-file scaffolding for the Next.js app, database schemas, and browser extension background scripts.
- Cursor: Ideal for fine-tuning the UI components, chat interfaces, and complex browser extension content scripts with inline diff reviews.

### Stack

- Frontend: Next.js with Tailwind CSS and shadcn/ui
- Backend: Next.js Server Actions and API Routes
- Database: Neon (Serverless Postgres with pgvector for RAG embeddings)
- Auth: better-auth
- Payments: None (Personal use clone)
- Other: Vercel AI SDK, Plasmo (Browser Extension Framework)

### Hosting

- Vercel (Hosting the Next.js web application dashboard and API endpoints): $0-20/mo
- Neon (Managed Postgres database with pgvector extension for knowledge base storage): $0/mo (Free tier)

### Build guide

1. **Project Initialization and Database Schema** — Scaffold the Next.js application with TypeScript, Tailwind CSS, and shadcn/ui. Set up Neon Postgres with pgvector and configure better-auth for secure user authentication.

```
Initialize a new Next.js project with TypeScript, Tailwind CSS, and App Router. Set up better-auth with email/password authentication using Drizzle ORM connected to a Neon Postgres database instance. Ensure the database schema includes tables for users, conversations, messages, knowledge_bases, and document_chunks with a vector(1536) embedding column using pgvector. Configure environment variables for database connection strings and AI provider API keys.
```

2. **Model-Agnostic LLM Router and ZenoChat Interface** — Build the chat interface and the backend orchestration layer using the Vercel AI SDK to support dynamic model selection between OpenAI, Anthropic, and Gemini.

```
Implement a chat dashboard UI mimicking ZenoChat in Next.js using shadcn/ui components. Create a backend model router utility using the Vercel AI SDK that accepts a selected model name ('gpt-4o', 'claude-3-5-sonnet', 'gemini-1.5-pro') and streams responses back to the client. Support system prompts, chat history persistence in Neon, and streaming UI updates.
```

3. **Knowledge Bases & RAG Pipeline** — Implement file upload processing, text chunking, embedding generation, and semantic vector search retrieval for user-uploaded documents.

```
Build a Knowledge Bases subsystem in Next.js that allows users to upload PDF and TXT files. Implement a server-side document parser that chunks text into overlapping segments, generates embeddings via OpenAI text-embedding-3-small, and stores them in the document_chunks table with pgvector. Implement a RAG retrieval function that performs cosine similarity search against user queries and injects relevant context into the ZenoChat system prompt.
```

4. **Visual Agent Builder & Workflow Automation** — Create a lightweight node-based or form-based builder for configuring custom AI agents with specific instructions, personas, and assigned knowledge bases.

```
Develop an Agent Builder interface allowing users to create custom AI personas with a name, description, system prompt, and linked knowledge base IDs. Store agent configurations in Neon. Update the ZenoChat execution route so that selecting an agent dynamically loads its prompt and RAG context before invoking the LLM router.
```

5. **Browser Extension Toolbar & Content Injection** — Build a Chrome browser extension using Plasmo or Manifest V3 that injects a floating toolbar into web pages for text summarization and rewriting.

```
Scaffold a Chrome extension using Plasmo with TypeScript and React. Build a content script that injects a subtle floating toolbar icon when text is highlighted on any webpage. When clicked, display a popup overlay offering options to rewrite, summarize, or explain the selected text by making authenticated API requests back to the hosted Next.js backend.
```

### Cost vs paying

**Starting costs (one-time):**

- Domain name (optional): $12 one-time
- AI API starting credits (OpenAI/Anthropic): $10 one-time
- Total: ~$22 one-time

**Ongoing costs (monthly):**

- Vercel Hobby / Pro Hosting: $0-20/mo
- AI API token usage (moderate personal RAG & chat): ~$5-15/mo
- Total: ~$5-35/mo

- Paying for the SaaS instead: $29.99/mo
- Build time: 35-50 hours
- AI tool credits: $20 (Claude Pro / Cursor Pro)
- Break-even: 2 months

## Sources

- [TextCortex Official Website & Scraped Content](https://textcortex.com)
- [PitchBook Company Profile — TextCortex AI](https://pitchbook.com)