# How to Vibe Code Your Own Helply (and Stop Paying for It) > The AI-Native B2B Support Platform - Site: https://groovehq.com - Category: Customer Support SaaS - Verdict: **Serious undertaking** (35/100 vibecodeable) - Estimated effort: 3-5 months of part-time work ## Verdict Build a simplified shared inbox subset, but keep paying for the real platform because the multi-source context layer and revenue intelligence engine require substantial engineering infrastructure. While an AI coding assistant can scaffold a basic support ticketing UI and simple RAG knowledge-base bot over a weekend, cloning Helply's core value is a serious undertaking. The difficulty lies in building the unified context data layer that continuously ingests, vectorizes, and correlates unstructured data streams from billing systems, call recorders, CRMs, and product analytics. Furthermore, engineering high-confidence guardrails that prevent LLMs from hallucinating incorrect support answers in high-stakes B2B environments involves intricate evaluation pipelines, robust background worker queues, and complex omnichannel webhook state management. ### What you can't replicate - Proprietary pre-built connectors and secure auth handling for dozens of third-party SaaS tools like Gong and HubSpot - Battle-tested enterprise security compliance, data residency, and uptime guarantees - Refined B2B prompt evaluation loops tuned over years of production support interactions ## What it does An AI-native customer support and revenue intelligence platform combining omnichannel ticketing with autonomous AI agents, multi-source context layers, and real-time revenue signal routing. ### Core features - Unified omnichannel inbox (Email, chat widgets, Slack Connect, WhatsApp) - Multi-source context ingestion layer (Knowledge base, ticket history, Slack, Stripe, Gong, PostHog, HubSpot) - Autonomous tier-1 AI agent resolution with confidence guardrails - AI co-pilot response drafting with inline account context citations - Real-time revenue signal scanning (churn detection, upsell requests, competitor mentions, plan-limit hits) - Cross-team routing engine (CSMs, AEs, product teams) - Outcome-based analytics dashboard and ROI calculator ## The business ### Pricing - AI-First Support: ~$1.00/ticket - Enterprise: Custom Founded 2011. Team size: 20-30. ## The hard parts - Building a low-latency multi-source context data layer that syncs and indexes unstructured logs from Stripe, Gong, and CRMs - Enforcing deterministic AI guardrails and confidence scoring to prevent catastrophic B2B hallucinated answers - Synchronizing real-time bi-directional message threads across asynchronous channels like email, chat widgets, and Slack - Real-time heuristic scanning of support conversations for nuanced B2B revenue and churn signals ## How to vibe code Helply ### Prerequisites - Node.js (free): Required runtime for modern full-stack TypeScript frameworks. - GitHub (free): Version control and repository hosting required for continuous deployment. - Anthropic API Key (Usage-based): Powers the core LLM reasoning, response drafting, and confidence scoring models. ### Recommended AI tools - Claude Code: Best-in-class terminal coding agent for scaffolding multi-file architectures, writing database schemas, and iterating on backend services. - Cursor: Essential for granular React component development, UI polish, and reviewing complex code diffs in the chat interface. ### Stack - Frontend: Next.js with Tailwind CSS and shadcn/ui - Backend: Next.js API routes paired with Inngest for background synchronization queues - Database: Supabase (Postgres with pgvector extension for context embeddings) - Auth: better-auth - Payments: Stripe - Other: Anthropic API for LLM agent tasks, Resend for transactional notifications ### Hosting - Vercel (Hosting the Next.js frontend and serverless API endpoints.): $20/mo - Supabase (Hosting the relational database, real-time channels, and pgvector context store.): $25/mo - Fly.io (Running background worker processes and persistent webhook listeners for third-party integrations.): $5/mo ### Build guide 1. **Database Schema and Authentication Setup** — Initialize the Next.js project with Supabase and configure better-auth for multi-tenant user management. ``` Scaffold a new Next.js project using App Router and TypeScript. Configure Tailwind CSS and set up Supabase as the database client. Implement better-auth with email/password authentication and organization tenancy tables (organizations, users, memberships). Ensure the database schema includes tables for tickets, messages, customers, and vector embeddings using pgvector. Write migration scripts and test database connectivity. ``` 2. **Unified Omnichannel Inbox UI** — Build the core shared inbox interface supporting list views, thread selection, and message dispatch. ``` Create a responsive SaaS dashboard layout in Next.js featuring a sidebar navigation and a three-pane ticketing view (ticket list, active message thread, and customer context sidebar). Implement real-time message updates using Supabase subscriptions. Build UI components for sending replies, updating ticket statuses (open, pending, closed), and assigning tags. ``` 3. **Knowledge Base & Context Ingestion Layer** — Build document ingestion pipelines that chunk knowledge base articles and store vector embeddings in Supabase pgvector. ``` Build an admin settings page and API route to upload and parse markdown knowledge base documents. Implement a background processing pipeline using Inngest that chunks documents, generates text embeddings via the Anthropic/OpenAI embedding API, and stores them in the Supabase vector table. Create a semantic search function that retrieves relevant document chunks based on incoming queries. ``` 4. **Autonomous AI Agent & Confidence Guardrails** — Implement the core AI agent logic to evaluate incoming tickets against context and determine resolution or human fallback. ``` Develop a backend agent service that triggers when a new ticket is created. The service must fetch relevant knowledge base snippets using pgvector similarity search, assemble a comprehensive prompt including customer metadata, and query the Anthropic API. Instruct the LLM to output a JSON response containing a confidence score (0-1), a draft response, and source citations. If confidence exceeds a strict threshold (e.g., 0.85), automatically resolve the ticket and send the reply; otherwise, save it as a draft for human review. ``` 5. **Revenue Intelligence & Signal Scanning** — Build real-time heuristics and LLM evaluation loops to scan incoming support text for churn language and upsell opportunities. ``` Implement a background processing worker that analyzes incoming customer messages for revenue signals: churn intent, upsell asks, competitor mentions, and plan-limit hits. Use structured JSON output validation from the LLM API to tag tickets automatically. Build an executive intelligence dashboard view that aggregates these tagged signals and correlates them with customer account value. ``` 6. **Integration Webhooks & Final Polish** — Configure inbound webhook handlers for external channels and perform end-to-end integration testing. ``` Build secure inbound webhook endpoints in Next.js to ingest messages from external channels (simulated email and chat widgets). Add robust signature verification, error handling, and retry logic using Inngest. Polish the user interface with loading states, error boundaries, and notification toasts. Write end-to-end test scripts for the ticket resolution lifecycle. ``` ### Cost vs paying **Starting costs (one-time):** - AI Coding Assistant Subscriptions: $40 - Custom Domain Registration: $12 - Total: ~$52 one-time **Ongoing costs (monthly):** - Vercel Pro / Hobby: $20/mo - Supabase Pro: $25/mo - Fly.io / Workers: $5/mo - Anthropic API Usage: ~$30/mo - Total: ~$80/mo - Paying for the SaaS instead: ~$300+/mo (scaled by ticket volume) - Build time: 60-90 hours - AI tool credits: $40 (Claude Pro + Cursor Pro) - Break-even: N/A (Built for custom control and technical learning) ## Sources - [Helply Official Website - Product & Pricing](https://groovehq.com)