Rivac LabsKeyword & Topic Extraction
Large bodies of text — research archives, customer feedback, meeting transcripts, industry publications — hold patterns that are invisible until someone extracts and counts them, and no team has the hours to read everything closely enough to spot a trend forming. This service builds a keyword and topic extraction pipeline that surfaces the terms, themes, and emerging patterns running through your text at scale, so you can see what's actually being discussed instead of guessing from a handful of examples. We tune the extraction to your domain vocabulary so it surfaces meaningful, specific terms rather than generic noise words, and can track how topics shift over time. It solves the problem of insight sitting buried in volume too large for any person to read end to end.
How We’d Approach This
A clear, staged plan — not a black box
- 1
Pull a representative corpus of your text and work with your team to define what a useful topic or keyword actually looks like in your domain
- 2
Pilot the extraction pipeline against that corpus, tuning it to surface domain-specific terms rather than generic stopword noise
- 3
Review the extracted topics and keywords with your team to validate they map to real, actionable themes
- 4
Deploy the pipeline against your live or growing text volume with trend tracking over time and a reporting cadence
What You Get
Deliverables from this engagement
- Production keyword and topic extraction pipeline tuned to your domain
- Initial topic map of your existing corpus
- Trend tracking showing how topics shift over time
- Reporting output (dashboard, CSV, or feed) fitted to how your team consumes it
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 Keyword & Topic Extraction