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Dataforest

enhanced
Carsoup

Entity Recognition

Carsoup

Product Company
Company Type
Minneapolis, United States
Location
Project work
Engagement Model
6 - 10 people
Team Size
6 - 9 Months
Duration
$50K - $100K
Budget

About

The online marketplace for cars wanted to improve search for users by adding full-text and voice search, as well as advanced search with specific options. We built a system application using Machine Learning and NLP methods to process text queries, and the Google Cloud Speech API to process audio queries. This helped greatly improve the user experience by providing a more intuitive and efficient search option for them.

Challenge, approach, and impact

Manual processing of unstructured text data

The client worked with large volumes of unstructured text data that required manual review and classification. Identifying names, locations, and domain-specific entities across documents was time-consuming and error-prone. The lack of automated entity extraction made it difficult to consistently structure text data, slowed down downstream analytics, and increased reliance on manual effort for information retrieval and data preparation.

How we built

Data Analytics and Visualization
AI & ML Solutions
ERP
Conversational AI
E-Commerce
Marketplaces
Architecture
Databases
API
Integrations

Testimonials

Brian Bowman

Carsoup

Verified Testimonial

Technically proficient and solution-oriented.

Team structure

Client team

Brian Bowman's avatar

Brian Bowman

President

Project stakeholder

The client stakeholders at Carsoup were working closely with the team at Dataforest

Agency team

2 x Machine Learning Engineer's avatar

2 x Machine Learning Engineer

Production

2 x Data Engineer's avatar

2 x Data Engineer

Production

1 x Product Manager's avatar

1 x Product Manager

Production

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