Company and Project Management
South Korea
Customer requirements, project scope, governance, communication, and final delivery management.
About Origin Data Lab
Tell Us Where Your Model Fails.
We Collect the Data It Needs.
We design targeted collection programs around the scenarios, environments, and edge cases your model needs to resolve.
We translate your target scenarios, locations, actors, sensors, metadata, and delivery requirements into a controlled field collection plan.
From skilled human workflows and precision manipulation to industrial, household, service, logistics, and mobility environments, we produce the real-world data your team cannot easily source internally.
Managed field operations in South Korea and Bangladesh, supported by our dedicated capture workflow, sensor-aware metadata pipeline, quality controls, and centralized processing infrastructure.
Start with a requirement brief, targeted sample, or focused evaluation collection.
No fixed package required. Initial scope review within 24 hours.
Built for fast, requirement-driven collection — from field capture
to structured, traceable delivery.
Custom Collection Partnership
Shape the data collection around your model
We work directly with AI teams to define the scenes, actors, locations, capture conditions, metadata, and output structure their models require.
Each engagement begins with a requirement brief and is converted into a targeted collection, quality-control, and delivery plan.
This is not a passive catalog purchase. The collection is designed around your model, evaluation objective, and operational constraints.
Requirement-to-Collection Workflow
We convert technical requirements into an executable field collection specification, including capture targets, metadata fields, quality thresholds, and delivery structure.
- Define target scenarios, actors, locations, and failure conditions
- Set capture, sensor, metadata, and quality requirements
- Deliver traceable data aligned with the agreed specification
Team Structure
Our team connects customer requirements directly to field execution, data processing, quality control, and structured delivery.
- Data Strategy — requirement analysis and project scope
- Data Engineering — ingestion, metadata, automation, and QC pipeline
- Field Operations — local collection planning and execution
- Quality Control — segment validation and specification compliance
- Partner Delivery — samples, documentation, and dataset handoff
We make the collection process visible so customers can review how requirements are translated into field tasks, quality checks, metadata, and final delivery.
How We Operate on the Ground
Origin Data Lab connects customer requirements directly to field collection. We define the target environment, scenario, actor mix, capture method, metadata requirements, and quality thresholds before collection begins.
Local field operators then execute the collection plan through our dedicated capture workflow, while centralized systems manage upload, segmentation, metadata processing, quality control, traceability, and delivery preparation.
Depending on project scope, each capture and derived segment can include more than 200 available metadata fields across device, camera, GPS, IMU, timing, collection context, quality, scene, object, and lineage layers.
Collection can be adapted by task, environment, participant profile, viewpoint, capture platform, mounting method, sensor configuration, activity complexity, repetition rules, and customer-defined acceptance criteria.
Each project can begin with a small targeted sample before expanding into a larger production collection.
The result is not merely raw footage, but a traceable data package produced against an agreed collection and delivery specification.
A controlled requirement-to-delivery pipeline — from customer specification to field execution and structured handoff.
Our proprietary capture workflow turns project specifications into structured field tasks with video, sensor, device, location, and operational metadata.
Capture, upload, segmentation, validation, metadata processing, and delivery are managed as one connected workflow.
Our Singapore-based infrastructure supports centralized ingestion, structured processing, traceability, and controlled dataset delivery.
Raw captures are transformed into structured records through software-enabled metadata enrichment, quality scoring, validation, and project-specific output preparation.
How We Maintain Consistency Across Field Operations
Project briefs are converted into repeatable field instructions so operators can follow the same capture, metadata, and quality requirements.
Captures are centrally uploaded, linked to their collection context, checked against project requirements, and tracked through one processing workflow before delivery.
Local field operators carry out customer-defined collection tasks using repeatable capture instructions and quality requirements.
Collected data is aggregated into one operational pipeline for metadata processing, quality validation, traceability, and delivery.
Training, Standards, and Field Readiness
Custom collection only works when technical requirements can be executed consistently in the field. Our training process converts each project specification into practical capture instructions, acceptance criteria, and field procedures.
Review our Data Services and Field Collection Standards for technical delivery, metadata, quality, consent, privacy, and field execution requirements.
Operational Collection Footprint
Origin Data Lab operates managed field-production capabilities in South Korea and Bangladesh, with centralized processing, quality control, traceability, and structured delivery.
Active Field Collection
Bangladesh
Scalable on-the-ground field production across industrial, commercial, household, service, mobility, and other project-defined environments, with local recruitment, training, capture execution, QC, and recollection support.
Processing and Delivery
Cloud Infrastructure
Centralized ingestion, segmentation, metadata enrichment, quality validation, documentation, and controlled project-specific delivery.
Who We Build Custom Data For
We work with teams that need real-world data unavailable in public datasets, difficult to reproduce in simulation, or too specific to obtain through standard catalogs.
Human Demonstration & Multimodal AI
Egocentric, task-centered, stereo, wearable, and sensor-aligned human data for activity understanding, hand-object interaction, tool use, manipulation learning, multimodal modeling, and embodied intelligence.
Robotics & Physical AI
Human demonstration, spatial, sensor, and environment data for manipulation, navigation, human interaction, obstacle handling, localization, scene understanding, and embodied intelligence.
Applied Research & Model Evaluation
Targeted data for benchmark creation, domain adaptation, failure analysis, long-tail scenario testing, and model validation in unfamiliar environments.
Trust is designed, not claimed
Consent, provenance, usage boundaries, and collection context belong in the pipeline — not in a PDF added after the fact. We design these controls into each collection program from the start.
Each project can preserve traceable links between collection requirements, field execution, source captures, metadata, processing history, quality decisions, and delivered outputs.
Current Collection Capability
These figures demonstrate the operating capacity and pipeline readiness behind our custom collection work. They do not represent a fixed catalog: each customer project is scoped, collected, processed, and delivered against its own requirements.
Operational collection statistics are automatically updated from the latest inventory.
Demonstrated Collection Capacity
317+ hours collected
Our internal field operations demonstrate the ability to coordinate continuous capture, preserve source footage, and convert it into structured segments through the same pipeline used to prepare customer-specific collections.
• 7,507+ source videos processed
• 76,154+ structured segments generated
• Source footage preserved for project-specific segment extraction
Scenario Execution Capability
Egocentric, industrial, service, household, logistics, and mobility workflows
Our field workflow can be configured around customer-defined tasks, environments, participant profiles, viewpoints, capture platforms, sensors, metadata requirements, activity complexity, and difficult model conditions.
• First-person and project-defined capture viewpoints
• Industrial, commercial, service, household, and logistics tasks
• Video, audio, IMU, sensor metadata, and structured capture records
• Customer-defined QC, traceability, and recollection rules
Geographic Execution
South Korea and Bangladesh field-production capability
South Korea supports specialized industrial and skilled-work collection, including task development and capture validation. For suitable projects, validated capture instructions and quality requirements can be adapted for cost-efficient, managed field production in Bangladesh. Additional locations can be evaluated according to project scope, field feasibility, and customer demand.
• South Korea: regional, skilled, industrial, commercial, and household workflows
• Bangladesh: scalable managed field operations across diverse environments
• Additional locations evaluated by project requirement and feasibility
What real-world data is your model missing?
Share the environment, scenario, actor, sensor, metadata, or failure condition you need. We will assess how it can be collected, processed, validated, and delivered.
Begin with a focused requirement review or targeted sample before scaling into a larger collection.
What helps us scope your collection
Target environment, failure scenario, geography, capture method, required metadata, quality threshold, expected volume, delivery format, and timeline.
A partial specification is enough for an initial feasibility review.
No fixed package required. Initial feasibility response within 24 hours.