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

> Customer Intelligence Platform

- Site: https://dovetail.com
- Category: Customer Intelligence & User Research
- Verdict: **Serious undertaking** (45/100 vibecodeable)
- Estimated effort: 3-6 months of serious part-time work

## Verdict

Build a simplified research note-taking app with basic RAG, or keep paying—replicating the multi-modal media transcription pipeline, automated PII redaction, and enterprise integrations requires serious engineering.

Dovetail is a heavy enterprise-grade system backed by $63M in funding. While a solo developer can spin up a Next.js frontend with Turso and OpenAI APIs in a weekend, building the asynchronous transcription queue, speaker diarization, multi-modal PII redaction, semantic chunking pipelines, and Slack bots that match their scale is a multi-month engineering marathon. You will constantly hit walls around media processing timeouts, token context limits, and complex relational permissions.

### What you can't replicate

- SOC 2, ISO 27001, and HIPAA compliance certifications
- Native enterprise connectors for 38+ enterprise tools (Salesforce, Zendesk, Jira)
- Extensive enterprise customer trust and brand footprint

## What it does

An AI-powered customer intelligence and user research platform that centralizes fragmented customer feedback into a single repository and uses LLMs to transcribe, classify, query, and generate insights.

### Core features

- Multi-modal media upload & asynchronous transcription queue
- Semantic vector search & RAG across qualitative text repositories
- AI Channels automated text clustering and opportunity tracking
- AI Chat natural language querying across workspace data
- AI Docs generative report creation with embedded video clips
- Slack and Teams bot integration for instant querying

## The business

### Pricing

- Free: $0
- Enterprise: Custom

### Funding

$63M raised.
- Series A ($63M in 2022)
Investors: Accel, Blackbird, Felicis Ventures, Grok Ventures

Founded 2017.
Team size: 50–200+.

## The hard parts

- Asynchronous media transcription, diarization, and automated PII redaction across video/audio layers
- High-throughput vector embedding pipeline and chunking strategies linked to granular project permissions
- Real-time bidirectional Slack/Teams bot message routing and event loops

## How to vibe code Dovetail

### Prerequisites

- Node.js (free): Required runtime for the Next.js full-stack application.
- GitHub (free): Source code management and deployment pipelines.

### Recommended AI tools

- Claude Code: Agentic terminal coding tool capable of scaffolding complex full-stack Next.js applications and multi-file architectures.
- Cursor: AI-native code editor for reviewing diffs and making rapid iterative UI updates.

### Stack

- Frontend: Next.js with Tailwind CSS and shadcn/ui
- Backend: Next.js Server Actions & API Routes
- Database: Turso (SQLite at the edge with vector support via libSQL)
- Auth: better-auth
- Payments: Stripe
- Other: OpenAI API (Whisper & GPT), Anthropic API (Claude), Cloudflare R2 (Media storage)

### Hosting

- Cloudflare (Hosting Next.js frontend and static assets via Workers/Pages, and R2 object storage for media files.): $5/mo
- Turso (Serverless edge database for relational data, tags, and vector embeddings.): $0/mo

### Build guide

1. **Project Scaffolding & Database Schema** — Initialize a Next.js full-stack app with Tailwind CSS, shadcn/ui, better-auth, and Turso database client bindings.

```
Scaffold a new Next.js 16 application using App Router, TypeScript, and Tailwind CSS v4. Install shadcn/ui components including buttons, dialogs, dropdowns, tables, and tabs. Configure better-auth with email/password authentication connected to a Turso libSQL database. Create relational database schemas for users, projects, insights, feedback_items, and transcript_chunks with vector embedding columns. Set up clean folder structures for server actions, database queries, and UI components.
```

2. **Media Upload & Transcription Pipeline** — Build file upload handlers to store audio/video in Cloudflare R2 and trigger OpenAI Whisper transcription jobs.

```
Build a secure file upload component in Next.js that uploads audio and video files directly to Cloudflare R2 using pre-signed URLs. Create a background server action or queue handler that takes uploaded media, calls the OpenAI Whisper API to generate full text transcripts with timestamps, and splits the resulting transcript into semantic chunks stored in the Turso database with vector embeddings generated via OpenAI text-embedding-3-small.
```

3. **AI Channels & Text Clustering** — Implement automated text classification and theme extraction routines to group feedback items into opportunity channels.

```
Implement an AI analysis service that processes newly ingested feedback items and transcripts within a project. Use Anthropic Claude API (via Anthropic API) to cluster raw feedback text into recurring themes and product opportunities, assigning tags, sentiment scores, and confidence metrics. Build a kanban or list UI view showing AI Channels with trend tracking over time.
```

4. **Semantic RAG Search & AI Chat** — Build vector similarity search and a conversational chat interface to query customer feedback repository data.

```
Develop a RAG-powered search and chat interface for the project repository. Implement semantic vector search querying the Turso libSQL vector store against user queries. Build an AI Chat sidebar component that accepts natural language questions, retrieves relevant transcript highlights, and uses the Anthropic API to generate cited answers referencing specific customer clips and quotes.
```

5. **AI Docs Generator & Export** — Create document generation workflows that compile chat findings, project highlights, and video clips into structured markdown docs.

```
Build an AI Docs editor module that allows users to generate structured documents (such as PRDs, VoC reports, and executive summaries) from workspace data. Implement inline chat editing features where users can prompt the AI to rewrite sections, automatically pulling in referenced highlight reels and embedded video timestamp clips. Ensure documents support collaborative commenting and presentation mode.
```

### Cost vs paying

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

- Domain registration: $12
- AI API starting credits (OpenAI / Anthropic): $25
- Total: ~$37 one-time

**Ongoing costs (monthly):**

- Cloudflare Workers & R2 Storage: $5/mo
- AI API usage (Whisper & LLMs): $15/mo
- Total: ~$20/mo

- Paying for the SaaS instead: $35+/user/mo
- Build time: 80-120 hours
- AI tool credits: $20/mo
- Break-even: 1 month of personal/team use

## Sources

- [Dovetail Official Website](https://dovetail.com)
- [Dovetail AI Docs Product Page](https://dovetail.com/ai-docs)
- [Dovetail Pricing Page](https://dovetail.com/pricing)