Forget LLMs. ORCA Is the Enterprise-Ready Future of Document AI

ORCA, Hyperscience’s Vision Language Model, delivers day-one document processing with no training required—just plug it in and start extracting. Unlike generic LLMs, ORCA supports accuracy targets, full data control, and human-in-the-loop verification for secure, high-volume enterprise use.

July 10, 2025

A common cold-start problem for machine learning (ML) based solutions is around model building. Specifically, software tasks cannot be completed without good models and good models require high quality data-sets which are accurately labeled. This means lots of upfront time invested on aggregating data, labeling work, and performance iteration.

At Hyperscience we have our very own Vision Language Model (VLM), we call it our Optical Reasoning and Cognition Agent (ORCA) model, which is the first of its kind and allows for:

No-Training Needed – Day 1 Processing: Save yourself weeks of document aggregation and annotations. Just specify which fields you want extracted and get results instantaneously.
Customer Accuracy Targets: You can set accuracy targets for any task and balance them with automation goals to get the most precise results.
Optimized for your Data: ORCA can learn and adapt to your documents and fields to get better at the task at hand so you’re not getting generic results from a model that doesn’t improve over time, like you would from a Large Language Model (LLM).

When LLMs were originally released to the public in 2022, they could only deal with text inputs. But with the recent pace of development, new Multimodal LLMs (MLLMs) and VLMs architectures have become the new norm, now supporting images, video, audio inputs in addition to text.

Suddenly, any medium of content can be supported without the hurdle of needing lots of upfront data, time, and iteration.

Considering the “wow factor” of VLMs/LLMs like ORCA, there are still many use-cases for specialized models! They’re amazing at dealing with large volume processing jobs, complex tables, and long-form text.

At Hyperscience we believe we can maximize customer goals, and provide time savings by leveraging both ORCA and our specialized models!

Common LLM/VLM Dangers

The biggest LLM providers in the game don’t offer the same capabilities as ORCA, here are some common challenges for any enterprise use-case:

You get what you get and you don’t get upset (no accuracy settings): Most LLMs don’t allow users to set accuracy targets; as a result, users don’t know what fields were incorrect or in need of review.
Hallucinations + No Human Oversight: Since other LLM providers don’t have the tools to help users locate mistakes, bad data gets passed downstream delaying important business processes. Users have no way of correcting machine errors.
Data Privacy & PII Protections: ORCA is always hosted safely within Hyperscience frameworks. Other LLMs ask you to send your PII data to third party servers without your oversight, with varying conditions about how your PII data can be used to improve their models, and no control on how long they can retain your data.

Avoid LLM Dangers with ORCA

At Hyperscience we’re the first in the Intelligent Document Processing (IDP) space to offer all these features in a single one-stop-shop model.

Human-in-the-loop support: Native support to correct and verify any data based on your accuracy goals. No fear of hallucinations making it to production.
Full control of your data: With ORCA you’re not sending your data to a third party API, and hoping to avoid data leaks or having your data be used to train global models. You always have full control over the data you submit.
Enterprise ML Support: When other LLMs fail to provide you the correct answer, there’s no one to call for help. With ORCA you have the full Hyperscience team at your disposal for questions.

Why ORCA, Why Now?

ORCA provides a great solution to customers looking to deal with high variability in document formats with no-training required.

Best of all, ORCA offers flexibility as a VLM capable of comprehending information from a variety of content mediums including images, logos, and documents, with support for tasks past just extraction.

With ORCA there’s no wasted time building integrations to LLMs, RAG frameworks, or orchestration tools. It’s fully supported within our existing platform. ORCA is plug and play right now and works with our existing platform’s blocks and flows.