Data Collection
Custom speech, vision, and text programs designed for your specific AI needs.
The Collection Challenge
Collecting high-quality, diverse, and representative datasets at scale requires specialized infrastructure and ethical frameworks.
Recruitment Bottlenecks
Finding qualified participants across demographics, languages, and geographies extends collection timelines.
Privacy Compliance
Multi-jurisdictional consent requirements and data residency rules create legal complexity.
Statistical Bias
Convenience sampling creates demographic imbalances that reduce model generalization.
Multi-Channel Collection Infrastructure
We operate global collection networks spanning mobile apps, web platforms, field operations, and crowdsourcing—all with built-in quality control.
Mobile Collection
Native iOS/Android apps with offline-first architecture, automated validation, and participant incentivization systems.
Web Platforms
Browser-based collection for text, image uploads, and survey data with real-time quality feedback.
Field Operations
On-site data collection teams for controlled environments, sensor data, and specialized use cases.
Crowdsourcing
Vetted contributor networks with reputation scoring, skill certification, and automated quality gates.
Supported Data Types
From speech and vision to structured data, we collect across all AI modalities with modality-specific quality standards.
Speech & Audio
Multi-language recordings with speaker demographics, acoustic environments, and native speaker validation. Supports wake words, commands, conversational speech.
Image & Video
High-resolution visual data with controlled lighting, camera angles, and scene diversity. Supports object detection, facial recognition, scene understanding.
Text & Documents
Multilingual text corpus collection, document scanning, and handwriting samples. Supports NLP, sentiment analysis, entity recognition.
Sensor & IoT
Accelerometer, GPS, environmental sensors, and biometric data with precise timestamping and calibration metadata.
Built-In Quality Control
Every data point passes automated validation before delivery. Real-time quality dashboards and post-collection audits ensure consistency.
Pre-Collection Screening
Participant verification, device compatibility checks, and environment validation before data capture begins.
Real-Time Validation
Automated quality gates check file format, duration, resolution, and metadata completeness during capture.
Statistical Sampling
Expert review of random samples to verify automated checks and identify edge cases.
Post-Collection Audit
Demographic balance verification, outlier detection, and final compliance review before dataset delivery.
Collection at Scale
Proven infrastructure supporting enterprise data requirements across modalities and markets.
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