Project Title

AI Startup Diagnosis


By analysing a Startup’s Pitch Deck, the AI Startup Diagnosis can offer suggestions for improvement and guidance on next steps. This tool, primed with the mindset we use when building products for our clients, can answer further questions about the pitch deck and help guide your startup to the next level of validation.

Building the AI Startup Diagnosis tool was a hands-on and instructive experience. Major challenges cropped up when dealing with PDF processing and processing AI responses as structured JSON. Limited filesystem access on the server created roadblocks in PDF processing. To bypass this, we experimented with a temporary third-party storage, but eventually found Render to be the perfect fit for its built-in filesystem access.
This tool is using OpenAI’s Embeddings and GPT-4 models to process the PDF content and extract revelant insights.
Furthermore, taking the AI’s raw output and parsing it into readable JSON was no small feat. We relied on Langchain’s StructuredOutputParser and OutputFixingParser, which allowed defining an expected structure and adding a fallback in case the output was unparseable.

The AI Startup Diagnosis tool embodies Whitesmith’s guiding principles: it looks at crucial aspects like market size, current revenue or earnings, team composition, company growth and MVP / roadmap, and blends in Whitesmith’s ethos. By focusing on the central problem a product aims to solve, understanding user feedback, and setting clear milestones, this tool goes beyond initial analysis. It’s like having a conversation with a Whitesmith advisor right at your fingertips, providing comprehensive startup guidance each step of the way.



Svelte, OpenAI, LangChain.js, Qdrant