#1: Launch a SaaS like ChatPDF or PDF.ai next week with Open Source

Dive into the growing market of 'Chat with PDF' tools, and learn how to build your own using open source tech!

Wait... why build something that’s already there?

Most successful SaaS products weren’t the first of their kind - think Slack, Shopify, Zoom, Dropbox, or HubSpot. They didn’t invent team communication, e-commerce, video conferencing, cloud storage, or marketing tools; they just made them better.

So what are "Chat with PDF" tools?

They are AI-powered PDF assistants that let you upload a PDF and ask questions about its content. You can summarize articles, extract key details from a contract, analyze a research paper, and more. To see this in action or dive deeper into the tech behind it, check out this YouTube video.

Let's look at the market!

Made possible by advances in AI like ChatGPT and Retrieval-Augmented Generation (RAG), PDF chat tools started gaining traction in early 2023 and have seen consistent growth in market interest, which is currently at an all-time high (source):

Keywords like "chat PDF" and "PDF AI" get between 1 to 10 million searches every month (source: google keyword planner), with a broad target audience that includes researchers, students, and professionals across various industries.

Leaders like PDF.ai and ChatPDF have already gained millions of users within a year of launch, driven by the growing market demand, with paid users subscribing at around $20/month.

Alright, so how can we build this quickly?

The core tech for most PDF AI tools are based on the same architecture. You generate text embeddings (AI-friendly text representations; usually via OpenAI APIs) for the uploaded PDF’s chapters/topics and store them in a vector database (like Pinecone).

Now, every time the user asks a question, a similarity search is performed to find the most similar PDF topics from the vector database. The selected topic contents are then sent to an LLM (like ChatGPT) along with the question, which generates a contextual answer!

Here are some of the best open source implementations for this process:

• GPT4 & LangChain Chatbot for large PDF docs by Mayo Oshin

• MultiPDF Chat App by Alejandro AO

• DocsGPT by Arc53

• h2oGPT by H2O.ai

Worried about building signups, user management, payments, etc.? Here are my go-to open-source SaaS boilerplates that include everything you need out of the box:

• SaaS Boilerplate by Remi Wg

• Open SaaS by wasp-lang

How will my SaaS stand out in the noise?

Here are a few strategies that could help you differentiate and achieve product market fit (based on the pivot principles from The Lean Startup by Eric Ries):

1. Narrow down your target audience for a personalized UX: For instance, an exam prep assistant for students with study notes and quiz generator; or a document due diligence and analysis tool for lawyers.

2. Add unique features to increase switching cost: You could autogenerate APIs for the uploaded PDFs to enable remote integrations (eg. support chatbot knowledge base); or build in workflow automation features for bulk analyses of PDFs.

3. Offer platform level advantages: You could ship native mobile/desktop apps for a more integrated UX; or (non-trivial) offer private/offline support by replacing the APIs with local open source deployments (eg. llama for LLM, an embedding model from the MTEB list, and FAISS for vector search).

TMI?

I’m an ex-AI engineer and product lead, so don’t hesitate to reach out with any questions!

P.S. I started this free weekly newsletter to share open-source/turnkey resources behind popular products (like this one). If you’re a founder looking to launch your next product without reinventing the wheel, please subscribe :)

---