Put your text to work automatically
Most businesses sit on more text than anyone can read: support tickets, reviews, emails, survey responses, chat logs, contracts. NLP turns that pile into structured signals — categories, entities, sentiment, priorities — that flow into your workflow instead of a backlog.
We match the technique to the job. Some tasks are best handled by fast, cheap classifiers; others genuinely need a large language model. We'll recommend the simplest approach that meets your accuracy bar.
- Classify tickets, emails or messages by topic, intent or urgency
- Extract names, dates, amounts, SKUs and other entities from free text
- Summarize long threads, documents or call transcripts
- Sentiment and theme analysis across reviews and survey responses
- Auto-route incoming messages to the right person or queue
- Deduplicate and cluster similar items at scale
Accuracy you can measure and trust
Text is messy, and no NLP system is right 100% of the time. We build with that reality in mind: the system can flag low-confidence cases for a human instead of guessing, which keeps the automated results reliable.
We evaluate on real examples from your data, share precision and recall in plain terms, and tune toward the errors that matter least to your business — for example, favoring a human review over a wrong auto-close on a sensitive ticket.
- Evaluation on a labeled sample of your actual text
- Confidence thresholds that route uncertain items to a person
- Precision/recall reported in plain language, not jargon
- A feedback loop so corrections improve the system over time
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Frequently asked questions
Can it handle our industry's specific terminology?
Yes — that's usually where the value is. General tools miss domain terms, product codes and internal shorthand. We adapt the system to your vocabulary using examples from your own text, and we test it on your real cases before it goes live.
Will our text be sent to a third-party AI provider?
That's your call, and we design around it. We can use hosted models, or run open models on infrastructure you control when the data can't leave your environment. We'll walk you through the trade-offs on cost, quality and privacy in the consultation.
How accurate will it be?
It depends on the task and how clearly the categories are defined — routing by topic is usually very reliable, nuanced judgment calls less so. We won't promise a number up front; we measure it on your data and show you the real results before you commit to rolling it out.