Rivac LabsNamed Entity Recognition & Text Classification
When a business runs on unstructured text — support tickets, contracts, news mentions, research notes — the first real bottleneck is just knowing what's in each document: which company, which person, which product, which category it belongs to. This service builds custom named-entity recognition and text classification models tuned to your specific entities and categories, not the generic people/places/organizations a stock NLP library recognizes, so you can automatically tag and route text the way your business actually needs it categorized. It's the layer that turns a pile of unstructured text into something you can filter, search, and route without a person manually reading and tagging every item. Clients use it to power automated routing, structured search, and downstream analytics that would otherwise require an army of manual taggers.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Define the exact entity types and categories that matter to your business, and label a representative sample of source text with your team
- 2
Pilot a custom NER and classification model against that labeled sample, tuned to your specific entities rather than generic off-the-shelf categories
- 3
Review model errors and edge cases with your team to refine entity definitions and classification boundaries before scaling
- 4
Deploy the tagging pipeline into your live text flow, wired into routing, search, or downstream systems, with monitoring for accuracy over time
What You Get
Deliverables from this engagement
- Custom-trained entity recognition and classification model
- Labeled dataset used for training and validation
- Integration into your routing, search, or downstream systems
- Accuracy benchmarks and ongoing drift monitoring
Six Ways We Could Architect This
Different engagement, different build — pick the shape that fits
There’s more than one way to deliver on this service. Browse a few of the ways we’d structure the work, depending on your speed, budget, and integration needs.
Ready to get started?
Tell us what you’re trying to get done and we’ll help you find the highest-leverage place to start — scoped small enough to prove itself before you commit to anything bigger.
Talk to us about Named Entity Recognition & Text ClassificationMost engagements like this start as a $500–$2,500 pilot — see full pricing.