Text & sentiment analysis (NLP)

What is text and sentiment analysis?

Much of the most valuable information about your customers lives in free text: service-centre enquiries, reviews, open survey answers and call transcripts. Text analysis (NLP — natural-language processing) uses AI to read all of these texts automatically, classify them by topic, detect the sentiment — positive, negative or neutral — and extract trends and insights that are impossible to see by reading manually.

How it works

We connect to your organisation's text sources — the ticketing system, emails, surveys or reviews — and run language models tuned to your language and business terminology. Every text receives a topic classification, a sentiment score and relevant tags, and the results are loaded into the data warehouse and presented in dashboards: which topics are rising, how sentiment changes over time, and where intervention is needed.

Who it's for

The solution suits any organisation receiving a high volume of customer text: service centres that want to route enquiries automatically and spot frustrated customers in time, product managers who want to know what people complain about and ask for, and marketing teams tracking reviews and satisfaction. Wherever "there's no time to read everything" — the AI reads everything.

The business benefit

Text analysis turns qualitative feedback into a quantitative metric you can manage: early detection of service and product issues before they spread, fast and accurate ticket routing that shortens handling times, and a true understanding of the voice of the customer — not a sample of ten calls, but the full picture of all of them.