Search Relevance

Create best-in-class search powered by data

Appen supports a wide range of search use cases and provides data across the entire lifecycle

Data Sourcing

We can source large volumes of high-quality data. We have pre-labeled datasets that get you started right away or we can collect new data that is unbiased, globally representative and specific to your content relevance application.

Data Preparation

We can annotate all your data types. Our products are equipped to handle image, video, audio, text, 3D sensor and multi-modal data, and our in-house team and local crowd expertise can ensure you get the right outcomes the first time.

Model Evaluation

We can perform user testing once your product is in production and benchmark how it performs against competitors. If you have a gap in performance, we can source and prepare the data required to have you performing at your best.

VIDEO: Learn more about powering your search relevance algorithms with high-quality data.

Trusted by global leaders to power their mission-critical AI with data for over 25 years

Relevance

Ads Evaluation ensures your content and landing pages are relevant to the query, context and culture of your target audience
Whole Page Evaluation determines how well your page performs – to user intent and against your competitors
Side-by-side Evaluation enables you to confidently deploy model updates after validating delivery of better results in a blind test

Cataloguing

Taxonomy Development ensures your customers' search terms and your tags are aligned, to improve content recommendations
Categorization ensures similar offerings are grouped and displayed at the same time (e.g., similar songs or video content)
Support across all data types including image, video, audio, text and multimedia

Content Moderation

Newsfeed and Social Media evaluations ensure content is credible and reliable
Related Search identifies auto-fill and auto-correct suggestions, as well as identifying “junk” or irrelevant content

Map and Navigation Search

Geo-Local Evaluation ensures the latest local results appear
Map Verification ensures point-to-point navigation is accurate, safe and efficient
Entity Evaluation and Correction ensures accurate business information (e.g., websites, hours, contact details)

Over 10 years' experience as the market leader for content relevance projects

Our search relevance expertise will ensure your AI-powered search engines are delivering the best results for your audience

Large scale

In-house data experts who manage delivery of 1B+ content relevance judgments each year for the largest technology companies.

Globally representative

Our crowd contains 1M+ contributors across 235+ countries ensuring your product can provide accurate results for a global audience.

Local expertise

Exclusive use of local, in-market experts with option to specify multiple interlocking demographics to ensure data is aligned with your target market.

Trust

State-Of-The Art Data Privacy and Security

On-site secure data annotation and collection capabilities in Europe, US and Asia
Global work-from-home secure workspaces and single sign-on capabilities
Data privacy and security compliant, holding all major accreditations and certifications

Quality

High-Quality Results Delivered Consistently

Track record of delivering high-quality results at large scale for long-standing customers
Proven methodology and expertise to measure and delivery quality results
Reduced bias in results thanks to our globally representative workforce of over 1M in 170+ countries
Built-in features that monitor and improve quality during and after annotations

Usability

Easy to use Data for AI Lifecycle Platform

Variety of delivery models, ranging from self-service on our platform to fully outsourced
Intuitive Graphical User Interface with annotation job templates and 24/7 support
Powerful API integrations to connect into your existing MLOps infrastructure

Scale

Proven Ability to Scale Large Data Batches Across All Use Cases

Over 25 years of working with world’s largest and most innovative AI companies
Broad and deep data modality support
Over 1M crowd workers provide unmatched workforce diversity and scalability

Speed

High-Quality Training Data Accessible at Greater Speed

Pre-labeling powered by machine learning models to increase data annotation speed
Workflows to automate complex multistep tasks and sequential jobs

Secure Data Access

Data security requirements are met for customers working with personally identifiable information (PII), protected health information (PHI), and other sophisticated compliance needs.

Enterprise-level security to protect sensitive client data

Secure Crowd

We offer a suite of secure service offerings with flexible options to ensure data security via secure facilities, secure remote workers, and onsite services to meet specific business needs.

Enterprise-level security to protect sensitive client data

Secure Facilities

We have sites in multiple geographies to support projects with Personally Identifiable Information (PII) and other sensitive data, as well as the right people, policies, and processes in place for a range of security levels, up to government level certification.

Enterprise-level security to protect sensitive client data

Secure Workspace

With our ISO 27001 accredited remote Secure Workspace solution, our global crowd can work on your sensitive projects remotely, without having to access a physical secure facility. This allows the diversity of our remote crowd to reduce bias and support multiple languages even through global disruptions.

Enterprise-level security to protect sensitive client data

Case Studies

See how Bing ensures their search results are culturally relevant

Read case study

Case Studies

Adobe uses image training data to develop a model which identifies the best stock images to use in marketing materials, making their library of 200 million assets easily discoverable.

Read case study

Latest News and Resources

Press Releases

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The White House’s Artificial Intelligence voluntary safety commitments missed the most essential component in the safeguarding of AI: human oversight.