01
Image annotation
Object tagging, bounding boxes, and scenario-based training for vision models.
Data, annotated within tolerance
A Jakarta-based micro team delivering annotation-intensive AI data work — reviewed against your guidelines before anything ships, and delivered with measured, verifiable quality.
Available for pilot projects · NDA-friendly
SPEC-00 · THE PREMISE
A focused team for detail-critical AI data work
Aethen AI is an Indonesia-based team providing AI data services with a focus on language-driven and annotation-intensive workflows: measured, reviewed, and signed by the people who did the work.
Guideline compliance: specs and guidelines reviewed before work begins, output checked against them before submission.
QA-led, not crowd-driven: a micro team means hands-on execution, accountable handling, no subcontracted batches.
Data-safe by design: happy to sign an NDA to protect your data from day one.
- 20+
- Contributors
- Jakarta
- Indonesia
- NDA
- Data-safe & ready
SPEC-01…06 · THE SCOPE
Core Services
End-to-end AI data services across image, video, audio, and LLM workflows — with QA built in.
02
Video & frame annotation
Frame-based annotation and video-related tasks where applicable.
03
Audio transcription
Transcription and audio-related tasks, including script-based recording projects.
04
LLM services
i18n support, RLHF-related annotation and evaluation, and prompt-level quality checks.
05
Safety red teaming
Red teaming and content evaluation to harden model behavior against misuse.
06
Quality Assurance
QA handling, feedback incorporation, and rework cycles to protect data quality.
APP-NOTES · APPLICATIONS
Industry Focus & Use Cases
After training AI models, we aim for results that apply across the following industries.
Language & Speech
Dataset support for Indonesian and English languages, including speech and text workflows.
Autonomous Driving / ADAS
Safety, trust, and multimodal annotation support for ADAS-related training data.
Multimodal AI & Moderation
Safety and trust workflows, including content moderation dataset support.
PROC-01…05 · THE DRAFTING PROCESS
Workflow & Quality Assurance
A simple, QA-led workflow that keeps delivery timely without sacrificing quality.
- 01
Task and guideline review
Review task specs and guidelines before work begins.
- 02
Annotation or data processing
Execute the annotation or data-processing work per guidelines.
- 03
Internal Quality Assurance
QA review against the guidelines before anything is submitted.
- 04
Feedback & rework handling
Incorporate client feedback through structured rework cycles.
- 05
Final delivery & version tracking
Deliver final outputs with clear version tracking.
We are comfortable adapting to updated guidelines and iterative feedback loops as requested by clients or partners.
TOOL-LIST · TOOLING
Tools & Platforms
As a micro team, we stay flexible on how to fulfill client requests and adapt to the tools you already use.
Spreadsheet-based tracking and QA
Internal documentation and communication
Client-provided annotation platform documentation
TERMS-00 · ENGAGEMENT
Engagement Model
- Pilot or trial-based onboarding: prove quality on a small scope first.
- Phase-based or batch delivery: aligned with your project milestones.
- Flexible workload: matched to project requirements and availability.
FIELD-01 · MEASURED DELIVERY
Our Works
W-01
Indonesian Script Recording Project
Short-sentence recording review based on client guidelines for an Indonesian-language audio dataset.
2,225Recordings completed
99.1–99.3%Passing rate
SIGNATORIES · THE TEAM
The Team
A native Indonesian micro team working under a Quality Assurance-led workflow — well-suited for pilot projects, small to medium batches, and phase-based delivery.
REQ-00 · REQUEST FOR QUOTE
contact@aethenai.com
Start a pilot
Send us your spec and we'll come back with a measured plan. Don't miss our updates — keep in touch.