2. • Privately owned and organically grown
• Headquarters: San Francisco, California
• Employees: 900+
• Customers: 35,000+
• Core business –Media Monitoring
History / Overview
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Founded: 2001 in Oslo, Norway with $15,000
• Strong top line growth since inception
• Consistently profitable every year of operation
• Mostly self-funded
• Yearly revenue 165M USD
Financials
Jorn
Lyseggen
• CEO & Founder
• Involved in four
startups to date
• Founded Meltwater in
2001
3. Offices All Around the Globe
• 50+ offices in Europe, North and South America, Asia, Africa, Australia
• 900+ employees, mostly sales
6. Help our clients track and understand
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own brand
competitors leads
partners
product reviews
own industry
Uses Meltwater to find out
about new instances of
vandalism and break-ins. Often,
the victim is in need of services
Uses Meltwater to help
determine how public
perception of certain ingredient
chemicals will influence
adoption & sales
Uses Meltwater to be alerted
of when certain patent will
expire in target markets
TV Station In India: Uses Meltwater to
monitor the performance and
popularity of news anchors and
programs
Uses Meltwater
social listening to
estimate and
prevent
infrastructure
attacks
7. Meltwater in Budapest
• Operations started in 2009
• No sales
• Originally a technology research group
• Currently two teams present:
• Content Services: responsible for content acquisition
• Data Enrichment: data analytics and enrichments (including NLP)
• Current size: 11, plan to grow to 20 by end of the year
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8. Our technology in numbers
• Content:
• News crawler: 250K+ sources, 2M+ documents daily
• Over 3 billion since 2001
• Blog crawler (icerocket.com): 30M blogs
• Social data: 100M+ document daily from various sources (twitter,
facebook, Youtube, comment streams, Wikipedia etc.)
• Data enrichment:
• NLP services in 12 languages (details later)
• Search and Storage:
• Ellastic Search index
• Riak – the largest know installation according to Basho
• ~150TB of data
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9. Existing NLP Services
● Language detection
53 Languages
● Sentiment analysis
● Key phrase extraction
12 languages with support
for numeric values
12 languages
● Named Entity Recognition
4 languages (English,
German, Swedish,
Norwegian)
● Content Categorization
12 Languages with support
for dynamic categories
● Intent detection
“I want to by an iPhone.”
PURCHA
SE
“How can I play music on my iPhone?”
QUESTION
Sales
Customer
Support
1 Language (English)
● Named Entity Disambiguation
1 Language
● Near duplicate detection
Language Agnostic
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10. NLP Capabilities under development
• Entity level sentiment
• Relationship extraction
• Document Grouping
• Searchable knowledge base
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