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Dataforest

enhanced

Image Recognition and Collecting Solution

MNDA

Private Company
Company Type
-, United States
Location
Project work
Engagement Model
6 - 10 people
Team Size
9 - 12 Months
Duration
$100K - $150K
Budget

About

Dataforest developed a solution that parses, processes, and collects images from Instagram. Each photo is processed and labeled with various tags like “blonde” or “curly hair”. The system is fully automated and runs the collecting as set by users. The high-tech model of image recognition provides only correct labeling without doubles, while the solution with an intuitive interface is easy for urther interaction with photos.

Challenge, approach, and impact

Manual image collection and labeling

The client collected and selected suitable images manually. Photos were sorted and labeled by hand, which required significant time and effort, was ineffective at scale, and limited the speed of creating image selections.

How we built

AI & ML Solutions
API
SaaS

Testimonials

Anonymous

Verified Testimonial

Working on this project, we built a fully automated image collection and labeling system that replaced manual workflows. The solution reliably processes large volumes of images, applies accurate tags without duplicates, and supports look-a-like search using a vector database. As a result, content selection became faster, more consistent, and significantly easier to manage.

Team structure

Client team

Anonymous's avatar

Anonymous

Product Owner

Project stakeholder

The client stakeholders were working closely with the team at Dataforest

Agency team

2 x Backend Developer's avatar

2 x Backend Developer

Production

1 x Machine Learning Engineer's avatar

1 x Machine Learning Engineer

Production

2 x Data Engineer's avatar

2 x Data Engineer

Production

2 x Product Manager's avatar

2 x Product Manager

Production

1 x Business Analytics's avatar

1 x Business Analytics

Production

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