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Unlimited flexibility to handleÂ
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Adaptive AutoML
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AI Solutions with Human Insight
Leverage human-labeled data and AIÂ
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Products
Data Labeling Platform
Unlimited flexibility to handleÂ
the most complex labeling needs
Adaptive AutoML
New
Human-in-the-loop workflowsÂ
with ML models
ML Platform
New
Tune better models faster.Â
Deploy in a few clicks
LLM & Solutions
Large Language Models
New
Bring your Language ModelsÂ
to the next level with human input
AI Solutions with Human Insight
Leverage human-labeled data and AIÂ
technologies to tackle businessÂ
challenges in your industry
Success Stories
10+ years of industry experienceÂ
solving real-world problems
AI DOMAINS
E-commerce Services
Search Relevance
Content Moderation
Computer Vision
NLP & Others
Field Data Collection
Data Labeling with LLMs
Pricing
Resources
Events
Join us at leading business andÂ
science conferences
Blog
Explore our updates, case studies,Â
technology articles and insights
Success Stories
10+ years of industry experienceÂ
solving real-world problems
Docs
Get Started
Tutorials
Code Recipes
API Reference
Python SDK
Toloka on Github
Knowledge Base
Crowdsourcing Concepts
What's new
Impact on AI
In the Industry
Responsible AI
Opensource
Public Datasets
Community
In Science
Toloka Research
Education Partnerships
Toloka Grant Program
Social Sciences
Impact on AI
Advancing the global AI communityÂ
by empowering professional growthÂ
and putting humanity at the center ofÂ
technology
Company
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BestPlace
Game-changing improvements in accuracy
Client
Challenge
Solution
Business impact
Accelerate your
e-commerce AI
Talk to our AI expert
Accelerate your
e-commerce AI
Talk to our AI expert
Client
AI-powered geo analytical tool for retail
App helps retailers and suppliers choose new store locations with end-to-end visibility of consumer patterns in a neighborhood
Data is collected and analyzed for over 40 patterns, such as transportation in the area, surrounding stores, number of households and cars, etc.
Clients include large retailers like Leroy Merlin and PepsiCo
Challenge
Issues with data collection and accuracy
Automated solutions extracted data from online maps and other sources
App accuracy was only 60% due to outdated data
Clients needed better accuracy for reliable predictions
Solution
Tolokers collect publicly available information about local neighborhoods
Up to 50,000 Tolokers complete field tasks at relevant locations
Verified data and current photos are uploaded to the system
BestPlace uses the up-to-date information to improve machine learning algorithms
Business impact
30% improvement in app accuracyÂ
with new data collection process
App accuracy now reaches 80–95%, depending on the client’s industry
Clients can review photos along with analytics for recommended locations
New results are a game-changer that enable clients to make informed decisions
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