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Company We organize the world’s attention & emotion


We are in a new era of the Internet. Static web pages are yesterday’s media. Now, business is driven by social messaging, conversations, and constantly flowing data. We call this The Stream.

As The Stream has emerged, the driving force of online attention has shifted from search to discovery, and from the static Web to social media and all forms of streaming data. But social conversations have also become overwhelmingly noisy; it’s getting harder to find what matters in all the chatter.

How do you make sense of this real-time landscape?

How do you filter signal from noise in the Stream?

Search engines are not the solution. They index the past, not the present. They’re great for finding Web pages, but no match for the real-time social Stream. We need a new approach: Trend Intelligence from Bottlenose.

In the enterprise, today’s real-time emergency is in marketing, due to the explosion of social expression affecting brands. However, soon all enterprise functions will operate under similar real-time pressures imposed by The Stream. Our Trend Intelligence solutions will take in all forms of stream data, internal and external, for a master, cross-correlated view of actionable trends in all the real-time forces affecting your business.

Bottlenose builds a real-time cognitive map of every topic, much like the human brain. It then uses sophisticated techniques for selecting and surfacing “trends with shove” from time-series data. We call this Trendfluence, allowing you to identify, anticipate and instigate trends that drive your business.

Think of Bottlenose Nerve Center™ as a Now Engine™. It scans and illuminates the present and shows you a live view of activity. It makes sense of what’s happening now, and helps you discover what’s important and what’s changing, as it happens, not after the fact.

Blend in historical data from Streams to replay past events as though they are happening now, to better understand past phenomena. Or use historical analysis to put emerging trends in a context of established patterns that shape your business.

Bottlenose Nerve Center™ spots real-time trends, tracks interests, measures conversations, analyzes keywords and identifies influencers. As we expand our library of data sources and aggregate the content, people, thinking and emotion of humanity’s connected communications, Bottlenose will map, reflect and explore the evolving global mind. We aim to continuously show what humanity is thinking and feeling, now.

Our Technology

The Secret Sauce

Our core intellectual property is called StreamSense™ (5 patents, 20+ pending). StreamSense™ is a real-time big data processing stack that automatically finds patterns in streams of data. This results in a continuous stream of intelligence insights and complex patterns that are derived from the data without needing to query or ask questions.

At any given point in time we are tracking billions of entities and do predictive analysis on 150 different metrics on each of these entities. These detected trends (thousands per minute) are then clustered and scored into more complex patterns and correlations.

The Secret Sause - Stream Sense

In order to make this possible, we have had to solve the three pillars of Big Data:

Volume: Ingestion of large amounts of stream data in real-time

  • Real-time ingestion of billions of messages per month, fully horizontally scalable.
  • Highly efficient and inexpensive cloud architecture.
  • Long term secure storage powered by Cassandra.

Variety: Support for many types of data, and generation of more data from the data

  • Discovers trends from unstructured or structured data streams such as social firehoses, news, broadcast TV and radio, enterprise data streams, stock market data, etc.
  • High-performance real-time data mining to extract entities from unstructured data streams and augment the data with new metadata.
  • Ability to configure and customize advanced metrics on the data. StreamSense generates 150 metrics and growing, including advanced sentiment, psychological profiling, average Nielsen scores for broadcast data, etc.

Velocity: Extremely high performance query and computing on live data

  • Real-time data ingestion and processing. Horizontally scalable.
  • Real-time filtering and streaming of rich data.
  • Historical insights are retrieved within seconds. No Hadoop jobs, ever. (Our platform can perform sub-second aggregations that would take more than an hour with Hadoop, for example.)
  • Ability to continuously aggregate and pull time series data. Capacity is horizontally scalable.
  • Real-time identification of new topics (NLP) without using dictionaries.
  • Live visualizations and co-occurrence graphing of entities and relationships in the data.

How Does StreamSense™ Work?

The StreamSense™ engine is composed of several different layers that run in the cloud. It leverages numerous big data storage and processing technologies like Cassandra, ElasticSearch, Redis and Storm.

The Secret Sause - Stream Sense Layers

The analysis process starts with Ingestion and Massive Data Mining. Data mining turns real-time unstructured data into more structured data. This not only results in stream data augmentations and extracted entities, but it also allows us to compile advanced metrics that, for example, combine demographic and psychographic insights. All events, entities and metrics are historically tracked, constantly updated, and instantly accessible at sub-second retrieval times.

Our data mining includes topic detection, link enriching, geocoding, named entity recognition, semantic classification, sentiment scoring, demographics analysis, psychological profiling, language detection, micro-content tokenization, etc.

In the Trend Graph & Detection layer we continuously keep track of all entities and their metrics. We do this by extrapolating time series data around entities using statistical approaches (like FFT) combined with machine learning heuristics (like SVM) to get a continuous stream of detection events around entities.

These detection events are then enriched with more context (related entities) and are then clustered and correlated to provide high-level overviews of new patterns.

Finally, there is the Agents layer in which we combine user configurations and interests to provide a continuous stream of intelligence events around people, topics, companies, competitors and industries.

The Team

Nova Spivack

Nova Spivack

Co-Founder, CEO

Serial Internet entrepreneur, expert on product development, search, social media and artificial intelligence. Co-founded EarthWeb in 1994 (IPO:1998), which also spun out (IPO:2007). First investor in Co-founded SRI nVention Incubator and worked on the DARPA CALO project (the original technology behind SIRI on the iPhone). Founded Lucid Ventures and (first consumer semantic search engine). Co-founded Live Matrix (Sold to OVGuide), The Daily Dot (the newspaper of the Internet), and StreamGlider (next-gen newsreader platform). Angel investor in Cambrian Genomics, Energy Magnification Corp. and Space Adventures. Advisor to Common Crawl Foundation, Publish This!, Sensentia. Worked at Thinking Machines and Kurzweil, Individual Inc. More than 50 patents. Flew to the edge of space in 1999.


Twitter: @novaspivack

Dominiek ter Heide

Dominiek ter Heide

Co-Founder, CTO

Has built complex information systems since age sixteen. Incubated numerous web products (big data, social and semantic web). Created and ran development teams in Europe, Japan and US. Former CTO of Cerego Japan ( Owner at (advisor to several startups in EU and Asia). Bachelor in Intelligent Systems Engineering.


Twitter: @dominiek

Board Members

Mark Toon

CEO of KPMG Capital.

John Frankel

Early stage venture capitalist at FFVC.

Andrew Jenks

Co-Founder Formation Data Systems.

Nova Spivack

CEO & Co-founder of Bottlenose,
serial entrepreneur / angel.

Dominiek ter Heide

CTO & Co-founder of Bottlenose.


Meet the team that’s making Bottlenose possible

Learn more about our investors at AngelList


We measure the world’s attention, and we get some, too.

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