How much do your model training labels solutions cost?
Our pricing is highly transparent and tailored to the expertise required for your specific tasks. For instance, LLM Math/Coding experts are $18/hr, STEM Generalists are $12/hr, Image Editing is $8/hr, Dense Captioning is $6/hr, and Road Lane annotation is $3/km. Abaka Forge platform credits are available at $0.20 USD each, ensuring scalable and predictable budget planning.
How fast can you deliver labeled training data?
We optimize for both speed and precision. Through the Abaka Forge platform and our massive global workforce, we routinely reduce data preprocessing time by 70%. Most standard projects begin scaling within 1 to 2 weeks after initial calibration, and individual annotators can achieve a max throughput of 500 files per day.
What modalities and output formats do you support?
We provide comprehensive model training labels solutions across Text, Image, Video, Audio, 3D/4D Point Cloud, and LiDAR + Camera fusion. We adapt to your exact pipeline requirements, delivering data in standard and custom formats such as JSON, COCO, XML, Parquet, and TFRecord, directly integrated via Abaka Forge.
How do you guarantee 99% accuracy for complex AI tasks?
We achieve 99% accuracy by deploying a scholar-network of vertically specialized annotators—such as mathematicians and developers—rather than general crowds. Combined with multi-layer QA, strict quality rubrics, and the large-model automation of Abaka Forge, we meticulously audit every dataset before delivery.
Are your annotation pipelines secure and compliant?
Yes, absolute data security is foundational to our model training labels solutions. We operate strictly within SOC 2 and ISO 27001 certified environments, ensuring full GDPR and CCPA compliance. Your data is processed through segregated secure pipelines under strict NDAs to prevent any unauthorized access.
Do you offer localized and multilingual annotation services?
Absolutely. Our extensive network includes over 1 million annotators distributed across 50+ countries. This global reach allows us to deliver highly accurate, localized text, audio, and conversational datasets tailored to specific cultural nuances and regional dialects for frontier AI applications.
How does Abaka AI differ from standard data labeling competitors?
Unlike traditional outsourcing platforms that rely on generic crowds and often pose IP risks, Abaka AI is a trustworthy data partner for frontier AI. We provide true domain experts, guarantee 0% copyright risk, and never build models that compete with you. We are self-funded, profitable, and focused entirely on your success.
How do you handle shifting requirements or change requests?
We maintain an agile approach to model training labels solutions. Through weekly syncs and direct access to dedicated project managers, you can seamlessly update annotation guidelines, refine quality rubrics, or pivot focus areas. Our flexible workforce quickly adapts to iterate alongside your rapidly evolving AI pipelines.
Can we run a pilot before committing to a massive dataset?
Yes, we highly recommend starting with a pilot phase. During Week 1–2, we deploy a specialized subset of annotators to calibrate our processes against your edge cases. This ensures our labeling quality and formats perfectly align with your expectations before we scale to full production volumes.
Who owns the labeled data after the project is complete?
You retain 100% ownership of your data and the resulting annotations. We ensure full IP provenance and zero copyright risk on collected data. Your data is exclusively yours—it is never repurposed, resold, or shared across other clients' model training labels solutions.
What tools do your annotators use to label the data?
Our teams utilize Abaka Forge, our proprietary, all-in-one platform for data collection, cleaning, and annotation. Abaka Forge enables up to 50x faster processing via large-model automation while supporting complex modalities like 3D point clouds, video spatial reasoning, and detailed RLHF interfaces.
Is there a minimum project size or volume requirement?
We accommodate a wide range of project sizes. Whether you need a small, highly specialized dataset for red teaming or millions of annotations for training a massive foundation model, our elastic scalability allows us to provision the exact workforce required for your model training labels solutions without arbitrary volume floors.