Earlybirdy - Seattle, WA

5

10

Amazon logo (vector)

As co-founder, Erik designed the semantic search engine, Earlybirdy. It delivers relevant results by parsing contextual data in real time. With its proprietary emotion algorithm and AI models, Earlybirdy predicts repeat purchase intent by revealing leading indicators of customer acquisition, retention, and churn—with 95% accuracy.

Earlybirdy was originally built on the Twitter API but can be used on any unstructured data.

Earlybirdy screenshot

Role

Co-founder, Product Designer

Dates

January, 2015 - June, 2015  •  6 months

Accomplishments

  • Built a team of 6 developers specializing in A.I. and data science
  • Seed-funded a startup from concept to MVP in 3 months
  • Created a new approach to natural language processing (NLP)
  • Designed an algorithm to find signal in noise in unstructured data
  • Achieved a combined relevance and confidence of 95%
  • Applied the algorithm to global public data at 1B posts per week
  • Negotiated a 1-year global Twitter firehose partnership
  • Built an automated net prompter score (NPS) for brands
  • Inferred buying intent for user acquisition, retention, and churn
  • Learned the risk of building a product on 3rd party data

Earlybirdy - Seattle, WA

Earlybirdy logo (vector)

Role

Co-founder, Product Designer

Dates

January, 2015 - June, 2015  •  6 months

Accomplishments

  • Built a team of developers specializing in AI/ML and data science
  • Seed-funded Earlybirdy from concept to minimum viable product (MVP)
  • Originated new ideas in natural language processing (NLP)
  • Designed a novel emotion algorithm that identified intent
  • Applied the algorithm to global public data at 1B posts per week
  • Negotiated a global Twitter firehose partnership
  • Integrated with the Twitter API
  • Built an automated net prompter score (NPS)
  • Inferred repeat buying intent for acquisition, retention, and churn
  • Achieved 95% accuracy in all results

5

10

As co-founder, Erik designed the semantic search engine, Earlybirdy. It delivers relevant results by parsing contextual data in real time. With its proprietary emotion algorithm and AI models, Earlybirdy predicts repeat purchase intent by revealing leading indicators of customer acquisition, retention, and churn—with 95% accuracy.

Earlybirdy was originally built on the Twitter API and can be used on any unstructured data.