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This is spot on, any legacy vendor focusing on a specific type of PDF is going to get obliterated by LLMs. The problem with using an off-the-shelf provider like
by kbyatnal 2y ago
This is spot on, any legacy vendor focusing on a specific type of PDF is going to get obliterated by LLMs. The problem with using an off-the-shelf provider like this is, you get stuck with their data schema. With an LLM, you have full control over the schema meaning you can parse and extract much more unique data.
The problem then shifts from "can we extract this data from the PDF" to "how do we teach an LLM to extract the data we need, validate its performance, and deploy it with confidence into prod?"
You could improve your accuracy further by adding some chain-of-thought to your prompt btw. e.g. Make each field in your json schema have a `reasoning` field beforehand so the model can CoT how it got to its answer. If you want to take it to the next level, `citations` in our experience also improves performance (and when combined with bounding boxes, is powerful for human-in-the-loop tooling).
Disclaimer: I started an LLM doc processing infra company (https://extend.app/ https://extend.app/)
- TeMPOraL 2y ago> The problem then shifts from "can we extract this data from the PDF" to "how do we teach an LLM to extract the data we need, validate its performance, and deploy it with confidence into prod?" A smart vendor will shift into that space - they'll use that LLM themselves, and figure out some combination of finetunes, multiple LLMs, classical methods and human verification of random samples, that lets them not only "validate its performance, and deploy it with confidence into prod", but also sell that confidence with an SLA on top of it.
- Cumpiler69 2y ago>A smart vendor will shift into that space - they'll use that LLM themselves It's a bit late to start shifting now since it takes time. Ideally they should already have a product on the market.
- TeMPOraL 2y agoThere's still time. The situation in which you can effectively replace your OCR vendor with hitting LLM APIs via a half-assed Python script ChatGPT wrote for you, has existed for maybe few months. People are only beginning to realize LLMs got good enough that this is an option. An OCR vendor that starts working on the shift today, should easily be able to develop, tune, test and productize an LLM-based OCR pipeline way before most of their customers realize what's been happening. But it is a good opportunity for a fast-moving OCR service to steal some customers from their competition. If I were working in this space, I'd be worried about that, and also about the possibility some of the LLM companies realize they could actually break into this market themselves right now, and secure some additional income. EDIT: I get the feeling that the main LLM suppliers are purposefully sticking to general-purpose APIs and refraining from competing with anyone on specific services, and that this goes beyond just staying focused. Some of potential applications, like OCR, could turn into money printers if they moved on them now, and they all could use some more cash to offset what they burn on compute. Is it because they're trying to avoid starting an "us vs. them" war until after they made everyone else dependent on them?
- deleted 2y ago[deleted]
- anon84873628 2y agoTo the point after your edit, I view it like the cloud shift from IaaS to PaaS / SaaS. Start with a neutral infrastructure platform that attracts lots of service providers. Then take your pick of which ones to replicate with a vertically integrated competitor or manager offering once you are too big for anyone to really complain.
- bayindirh 2y agoNever underestimate the power of the second mover. Since the development is happening in the open, someone can quickly cobble up the information and cut directly to the 90% of the work. Then your secret sauce will be your fine tunes, etc. Like it or not AI/LLM will be a commodity, and this bubble will burst. Moats are hard to build when you have at least one open source copy of what you just did.
- SoftTalker 2y agoAnd next year your secret sauce will be worthless because the LLMs are that much better again. Businesses that are just "today's LLM + our bespoke improvements" won't have legs.
- sitkack 2y agoSoftware is dead, if it isn't a prompt now, it will be a prompt in 6 months. Most of what we think software is today, will just be a UI. But UIs are also dead.
- cpursley 2y agoSoftware without data moats, vender lock-in, etc sure will. All the low handing fruit saas is going to get totally obliterated by LLM built-software.
- sitkack 2y agoTotally agree.
- fragmede 2y agoIf I'm an autobody shop or some other well-served niche, how unhappy with them do I have to be to decide to find a replacement, either a competitor of theirs that used an LLM, or bring it in house and go off and find a developer to LLM-acceleratedly make me a better shopmonkey? And there are the integrations. I don't own a low hanging fruit SaaS company, but it seems very sticky, and since the established company already exists, they can just lower prices to meet their competitors. B2B is different from B2C, so if one vendor has a handful of clients and they won't switch away, there's no obliterating happening. What's opened up is even lower hanging fruit, on more trees. A SaaS company charging $3/month for the left-handed underwater basket weaver niche now becomes viable as a lifestyle business. The shovels in this could be supabase/similar, since clients can keep access to their data there even if they change frontends.
- wraptile 2y agoThat's what we did with our web scraping saas - with Extraction API¹ we shifted web scraped data parsing to support both predefined models for common objects like products, reviews etc. and direct LLM prompts that we further optimize for flexible extraction. There's definitely space here to help the customer realize their extraction vision because it's still hard to scale this effectively on your own! 1 - https://scrapfly.io/extraction-api https://scrapfly.io/extraction-api
- quantumPilot 2y agoWhat's the value for a customer to pay a vendor that is only a wrapper around an LLM when they can leverage LLMs directly? I imagine tools being accessible for certain types of users, but for customers like those described here, you're better off replacing any OCR vendor with your own LLM integration
- panta 2y agoHow do you handle the privacy of the scanned documents?
- kbyatnal 2y agoWe work with fortune 500s in sensitive industries (healthcare, fintech, etc). Our policies are: - data is never shared between customers - data never gets used for training - we also configure data retention policies to auto-purge after a time period
- panta 2y agoBut how to get these guarantees from the upstream vendors? Or do you run the LLMs on premises?
- Karrot_Kream 2y agoIf you're using LLM APIs there are SLAs from the vendors to make sure your inputs are not used as training data and other guarantees. Generally these endpoints cost more to use (the compliance fee essentially) but they solve the problem.
- bitdribble 2y agoWith the docrouter.ai, it can be installed on prem. If using the SAAS version, users can collaborate in separate workspaces, modeled on how Databricks supports workspaces. Back end DB is Mongo, which keeps things simple. One level of privacy is the workspace level separation in Mongo. But, if there is customer interest, other setups are possible. E.g. the way Databricks handles privacy is by actually giving each account its own back end services - and scoping workspaces within an account. That is a good possible model.
- montecruiseto 2y agoSo why should I still use Extend instead of Gemini?
- MajorData 2y ago`How did you add bounding boxes, especially if it is variety of files?
- bitdribble 2y agoIn my open source tool http://docrouter.ai http://docrouter.ai I run both OCR and LLM/Gemini, using litellm to support multiple LLMs. The user can configure extraction schema & prompts, and use tags to select which prompt/llm combination runs on which uploaded PDF. LLM extractions are searched in OCR output, and if matched, the bounding box is displayed based on OCR output. Demo: app.github.ai (just register an account and try) Github: https://github.com/analytiq-hub/doc-router https://github.com/analytiq-hub/doc-router Reach out to me at andrei@analytiqhub.com for questions. Am looking for feedback and collaborators.
- raghavsb 2y agoGreat, I landed on the reasoning and citations bit through trial and error and the outputs improved for sure.
- pmarreck 2y agoI have some out-of-print books that I want to convert into nice pdf's/epubs (like, reference-quality) 1) I don't mind destroying the binding to get the best quality. Any idea how I do so? 2) I have a multipage double-sided scanner (fujitsu scansnap). would this be sufficient to do the scan portion? 3) Is there anything that determines the font of the book text and reproduces that somehow? and that deals with things like bold and italic and applies that either as markdown output or what have you? 4) how do you de-paginate the raw text to reflow into (say) an epub or pdf format that will paginate based on the output device (page size/layout) specification?