# Humata TechStack Analysis ## Tools found with [`openapi-devtools` Chrome Extension](https://github.com/AndrewWalsh/openapi-devtools) - https://nextjs.org/ - https://vercel.com/ - https://vercel.com/domains (https://www.whois.com/whois/humata.ai) - https://stripe.com/ - https://supabase.com/pricing - They use it for all auth, database and object storage - They send a verification email: - `Confirm your signup Please confirm your email address by opening the link: https://benzfodquatjcaxqhbmk.supabase.co/auth/v1/verify?token=XXXXXXX&type=signup&redirect_to=https://app.humata.ai` - The subdomain indicates they use the managed service - https://launchdarkly.com/ - DevOps tools, A/B tests, Feature flags, Session recording, ... - http://app.posthog.com - Similar to launchdarkly - http://api-iam.intercom.io - Not sure for what exactly - `iam` means `Identity and Access Management`, but they already use Supabase for that. ## Hacks - I circumvented their **free plan PDF 60 pages limit** by merging 4 pages into one using http://www.pdfdu.com/pdf-pages-merge.aspx and was able to upload the whole [EU AI Act](https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A52021PC0206) `PROPOSAL` (108 pages -> 27 pages) and `ANNEXES` (17 pages -> 5 pages). ## Insights ### LLM model used Their analytics tool https://clientstream.launchdarkly.com/ made a request and exposed their used LLM model: ```json patch {"key":"open-ai-model","value":"gpt-3.5-turbo"} ``` ### Cabability evaluation - A tricky question like **`give me only all the titles from the proposal document`** is hard because it would need to analyze all pages contents. - Instead it returned wrong output (some other `titles` mentioned in the document) that indicates Humata uses similarity search and does not have secret sauce algorithms. - Their internal steps are likely basic RAG: 1. Generate search queries from user question 2. Search backend using preprocessed documents 3. Generate chat response using augmented content ![image](https://user-images.githubusercontent.com/22003767/280467612-d4ce8422-740c-40ee-bf8e-44292a668bfd.png) ### Is Humata capable? - No, it is very basic and is unusable for complex legal document work as proclaimed by their [blog post](https://www.humata.ai/blog/how-to-use-ai-for-legal-documents). - Their service is a basic RAG with a nice website, although they don't even render messages as clean Markdown, thus the chat experience is very bad. - The only nice addition is the document view and highlighting on the right. - **The next screenshot underlines the unusefullness of the product.** ![image](https://user-images.githubusercontent.com/22003767/280469439-bb2751aa-4f42-48c2-9c76-d32b01e10a05.png) ![image](https://user-images.githubusercontent.com/22003767/280469826-4e05304a-25a3-4453-9849-a5bb2513124f.png) ## Conclusion - Robin got very excited about Humata, but it turns out, the general case as with most AI startups persists: "Their marketing is better then the product." - Robin wonders, once again, how easy it is for startups to get **$3.5M** fundraising from Google Ventures without any exceptional technology. - We can build a product on par with Humata. - One problem ComplyAI has is our current website design, branding work and vision **is not cohesive enough**. _We need better design._