FAQ
Frequently asked questions about Neural Context and its capabilities
If you can’t find an answer here, reach out to us via the Contact Us page.
Why do I need Neural Context?
A secure and fast infrastructure is the crux of every system. Your organization's data continues to increase and with every piece of data added, the difficulty in deciding which entities can see what data only gets exponentially more impossible. Neural Context allows you to handle incredible amounts of data, securely and efficiently as it classifies, sorts, and handles what other systems and human's cannot. Using our product, you're able to easily set your own classification rules and correctly categorize your documents. You'll be assured your information is secure and handled with highly efficient precision. You need Neural Context because you care about your data.
How does Neural Context Work?
The Neural Context process incorporates a strong algorithm to process and assess your
documents, emails, texts, memos, etc and classifies them. These documents and assessments
can be viewed and recalled via the Neural Context Dashboard.
How much does a Neural Context license cost?
Corporate and individual pricing will be different. Currently, you can reach out to us via
our Contact Us page for
detailed information. An online Neural Context pricing calculator is coming soon!
What can Neural Context do that a human can't?
Neural Context can semantic assess a document with equal or better semantic ability. It can
assess a million sentences in under 4 seconds. An average human would take 4 hours just to
read it. NC never gets tired and never forgets.
Is Neural Context fast?
Yes. It can assess a million sentences in under 4 seconds.
Is Neural Context accurate?
In testing, Neural Context achieves 90% accuracy. However, accuracy isn't the best metric
(
see this article for more information
). More meaningful statistics are precision, recall
and the F1 score (a balance between precision and recall). In tests, Neural Context has
achieved:
- 89% F1
- 80% recall
- 100% precision
How does Neural Context handle corner cases?
Neural Context works hand-in-hand with the user. At any point, you can identify false
positives and false negatives. NC will update the database, and its internal model,
immediately improving with every input.
What if I don't have tons of data, is Neural Context still a fit for me?
Absolutely. This is one of the biggest advantages to Neural Context. Our cutting edge
algorithm doesn't require massive amounts of data for training. We can handle both big and
small data sets.
What happens if Neural Context classifies my data incorrectly?
Neural Context works hand-in-hand with the user. At any point, you can identify false
positives and false negatives. NC will update the database, and its internal model,
immediately improving with every input. All corrections are logged and all Neural Context
classifications, guides, and assessments are stored in an encrypted database. This allows
for auditing and metrics extraction.
Can I test Neural Context?
Yes! A SaaS version with a sandbox is coming soon. It should be live mid-2026!
What different forms of media does Neural Context handle?
Neural Context's native language is Markdown but virtually any text-based document can be
used by converting into MarkDown. Neural Context provides a small open source service you
can run to convert documents from pdfs, word, etc. into MarkDown. You can find it here:
https://github.com/NeuralContext/nc-convert
What different forms of media will Neural Context handle?
Neural Context supports any text-based data that can be converted to MarkDown.
Why is Neural Context better than another basic LLM?
Speed, accuracy, cost, data consistency -- lots of reasons! Neural Context combines the
best of AI (LLMs), ML (Machine Learning), and Hu (Humans)! See our online presentation for
more information:
Is Neural Context difficult to set up?
Neural Context is completely containerized. We provide Helm charts or Kustomize files for
you to deploy. In the near future, a SaaS version will be available.