Feelingstream

Feelingstream

Feelingstream delivers real-time customer insight to help your business become more efficient, boost revenue and keep your customers coming back.

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DateInvestorsAmountRound
-investor investor investor investor

€0.0

round
investor investor

€0.0

round
investor investor

€0.0

round

N/A

Grant
Total Funding000k

Financials

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Revenues, earnings & profits over time
EUR2017201820192020202120222023
Revenues0000000000000000000000000000
% growth581 %(1 %)35 %7 %106 %(25 %)19 %
EBITDA0000000000000000000000000000
% EBITDA margin22 %(11 %)2 %54 %54 %(32 %)-
Profit0000000000000000000000000000
% profit margin18 %(15 %)(1 %)36 %39 %(62 %)-
EV0000000000000000000000000000
EV / revenue00.0x00.0x00.0x00.0x00.0x00.0x00.0x
EV / EBITDA00.0x00.0x00.0x00.0x00.0x00.0x00.0x
R&D budget0000000000000000000000000000

Source: Company filings or news article, Dealroom estimates

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More about Feelingstream
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Feelingstream, an Estonian company established in 2015, specializes in conversational analytics, leveraging artificial intelligence to process customer interactions from various channels like calls, emails, and chats. The company was founded by Terje Ennomäe, who currently serves as the CEO. Ennomäe's background includes experience in the banking and telecom sectors, where she identified the challenge of manually analyzing vast amounts of customer feedback, which directly informed Feelingstream's value proposition.

The firm's core business involves offering a transcription and analytics platform that converts unstructured customer communication into actionable data for large enterprises. This service primarily targets sectors with high volumes of customer interactions, such as banking, telecom, and utilities. Feelingstream's business model is centered on a B2B software-as-a-service (SaaS) subscription, providing its clients with tools to understand customer sentiment, identify reasons for contact, and improve service quality and efficiency.

The platform utilizes proprietary speech recognition technology specifically trained for the Estonian language, among others, to achieve high accuracy in transcription. Beyond simple transcription, the software analyzes the content to highlight key topics, trends, and potential issues, enabling businesses to move from reactive problem-solving to proactive improvements. For instance, the system can automatically classify interactions, measure script compliance in call centers, and detect sales opportunities. This analytical depth allows clients to reduce manual work, lower operational costs, and enhance the overall customer experience by making data-driven decisions.

Keywords: conversational analytics, customer feedback analysis, speech recognition, text analytics, AI, customer service intelligence, call center optimization, B2B SaaS, sentiment analysis, compliance monitoring

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