Customer support is a challenge that all products face at some point. You start making sales of your product because people love it, and before you know it, you are answering the same five questions again and again through every possible channel like email, Discord, Twitter DMs, etc. And scaling that isn't feasible at all; after all, hiring a support team when you have no money isn't really an option.
This is the problem we tried to solve with Doupple.
What is Doupple?
Doupple builds your customer support and lead generation AI agent. You give it your documents, links, or plain text, and it builds you a custom-trained AI agent capable of answering customer queries, guiding them through the use of your product, and collecting leads on your site.
For starters, make no mistake — this isn't some kind of drag-and-drop solution. You'll still have to plug in a script tag and do some minor configuration depending on your technology stack. What Doupple does eliminate, however, is the hard work, you won't need to create a RAG pipeline, handle vector embeddings, create the retrieval code, or run any back end in order to get an AI support agent that actually knows your product.
Deployment of your trained agent will take a few minutes on Next.js, React, WordPress, Shopify, Webflow, or even HTML.
Why we built it
As developers, most of us have either:
Rapidly built a very basic chatbot by integrating with the OpenAI API and realized very soon that although calling the API was easy 20%, the remaining 80% is chunking up the documents correctly, handling the embeddings, context windows, retrieval, and hallucination (if the model doesn't have context enough) and even building an admin panel to see what questions users ask.
Spent money on overkill (also expensive) enterprise-level customer support software like Intercom, Zendesk (but with AI). It's definitely overkill and over-priced for a small project, early-stage company, or even a side hustle validation project.
We wanted something that sits in the middle: give us the retrieval and training infrastructure so we're not reinventing it from scratch, but keep enough control that it doesn't feel like a black box glued onto our site.
How it works under the hood
1. Upload your knowledge base
Drop in your documentation, FAQ pages, product content, or even raw text. You can mix formats - a PDF here, a URL there, some manually written context for edge cases your docs don't cover.
2. The agent gets trained
Your content gets processed and indexed so the agent can actually reason about context, rather than doing basic keyword matching. This is the part that would normally take you a few days to build properly (chunking strategy, embedding model choice, retrieval tuning) - here it's handled for you.
3. Customize the flow
Set up conversation flows and lead-capture triggers - for example, auto-detecting when someone shares their email, asks a pricing question, or requests to be contacted, and routing that into a structured lead instead of losing it in a chat transcript.
4. Deploy
Add the script tag to your site, style it to match your branding, and it's live. You still touch code here - it's just a fraction of what building this from scratch would take.
The stack behind Doupple is built on Next.js 15, React 19, Supabase, and OpenRouter for model access, which means we're not locked into a single model provider - that flexibility matters as the LLM landscape keeps shifting month to month.
Who this is actually for
- Indie hackers and solo founders who need support coverage but don't have time to build a full RAG system on top of everything else they're shipping
- Small teams that can't yet justify $500+/month on enterprise support tooling
- Agencies that want to offer AI-powered support as a service to clients without building and maintaining the infrastructure themselves
- Developers validating an idea who want real user questions answered 24/7 without babysitting a chatbot
What it's not
It's not a magic zero-code solution, and we're not going to pretend otherwise. You'll still need to understand your stack well enough to drop in a script tag, configure it, and probably tweak a few things based on how your users actually talk. If you're looking for something with literally zero technical involvement, this probably isn't it. If you're a developer who wants to skip the painful infrastructure work and focus on the actual product experience, that's exactly the gap we're filling.
Try it
We're currently in beta, and it's free to get started - no credit card required.
We're actively building based on feedback, so if you try it and hit a rough edge, an error, or just have a suggestion, drop a comment here or reach out directly. We read everything, and being early means your feedback actually shapes what gets built next.
Have you built or used AI agents for support/lead capture before? Curious what part of the process gave you the most trouble - was it the retrieval/embeddings side, prompt reliability, or just getting leads to route somewhere useful? Would love to hear how others have approached this.
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