Im losing my mind trying to analyze these quarterly financial reports for my firm. I have like 50 PDFs that are 30+ pages each and trying to get ChatGPT to actually remember the data across all of them without hallucinating is just impossible. It keeps losing the context or messing up the table data and I honestly dont have the time to baby sit it. Ive looked into things like ChatPDF or Humata but they seem so hit or miss? Like I saw some reddit threads saying Humata is great for citations but then others say it crashes on anything over 10mb. My budget is pretty flexible, maybe up to 50 bucks a month if it actually works, but I need something that can handle large datasets without me having to feed it in manually piece by piece. Does anyone know of a wrapper or an actual tool that doesnt just choke on massive files? Or am I just stuck waiting for OpenAI to fix their own stuff...
^ This. Also, be careful with those web-based wrappers, they often lack the privacy controls you need for financial data. If you have the hardware, try running LM Studio locally on your machine with a high-context model like Meta Llama 3.1 70B. It keeps everything offline and away from third-party servers. If you prefer cloud, just use Claude directly instead of wrappers. It is way more reliable than most standalone tools right now.
Honestly, id be super careful uploading sensitive financial reports to random third-party sites. If you want something that actually handles large docs well, check out Claude 3.5 Sonnet instead of the basic chat wrappers. It has a huge context window and is way better at keeping track of data without hallucinating. Just make sure you read the privacy settings first, because you never know where that data is ending up...
Building on the earlier suggestion, i get the privacy concerns but honestly sometimes you need more power than local hardware offers for heavy lifting. I spent last quarter wrestling with 50+ page PDFs for a client project and realized that local models just couldnt handle the cross-referencing accurately enough. I ended up moving to a dedicated enterprise-grade cloud workspace where i could index the documents in a vector database before querying them. It was way more stable than trying to shove everything into a single chat window. If you go this route, look for platforms that allow you to manage your own API keys. It usually keeps the cost under that 50 buck limit too, since you arent paying a middleman for the convenience. Its a bit of a setup process but it stops the hallucinations cold because the model only pulls from your uploaded files.