How much do your AI training data company services cost?
Our pricing is transparent and highly competitive, tailored to the complexity of your requirements. For example, expert LLM Math/Coding annotation is $18/hr, general STEM tasks are $12/hr, and Dense Captioning is $6/hr. For custom datasets, pricing is per-unit, such as Stock Images at $0.01/img or 3D Indoor Scene scans at $100/scan. Abaka Forge credits are just $0.20 USD each.
How quickly can you scale an annotation pipeline for a new project?
We operate with rapid agility. Pilot programs and pipeline strategies are scoped within Days 0–3. By Week 2, we finalize multi-layer QA calibration, and by Week 3, we can deploy thousands of vertically specialized annotators across 50+ countries to meet massive volume demands.
What data modalities and output formats do you support?
We cover every major modality including Text, LLM RLHF, Image, Video, 3D/4D Point Cloud, LiDAR + Camera fusion, and Audio. We export to industry-standard formats such as JSON, COCO, Parquet, and TFRecord, directly integrated through our proprietary Abaka Forge platform.
How do you guarantee 99% accuracy on highly complex reasoning tasks?
Instead of crowdsourcing to generalists, we utilize scholar-network domains—hiring professionals and PhDs for Mathematics, Coding, and Medicine. We cap throughput at 500 files/day per annotator to prevent fatigue and implement rigorous multi-layer QA and objective benchmarks.
Is your data collection and annotation environment secure?
Absolutely. Our segregated secure pipelines are SOC 2 and ISO 27001 certified. We adhere strictly to GDPR and CCPA regulations, utilize comprehensive NDAs, and ensure your proprietary models and datasets never leak or face external exposure.
Can you provide localized data collection and multilingual transcription?
Yes, our expansive network of 1 million annotators spans over 50 countries, enabling us to capture nuanced, highly accurate multilingual data. Whether you need regional audio transcription at $7/hr or complex translated text pairs, we possess the global reach required.
How does Abaka AI differ from standard crowdsourced labeling services?
Unlike generalist platforms, we provide a 0% copyright risk guarantee and use vertically specialized scholars. We never build competing models, we are entirely self-funded, and we reduce your internal preprocessing time by up to 70% via the advanced automation of Abaka Forge.
How do you handle changes to the annotation guidelines mid-project?
We build elasticity into our workflows. During our weekly optimization syncs, you can update guidelines based on evolving model architecture. Our project managers immediately retrain specialized pods and adjust multi-layer QA rules to reflect your new edge cases seamlessly.
Do you offer a pilot phase before we commit to high-volume scaling?
Yes, we strongly recommend a pilot during Weeks 1–2 of our engagement. This calibration phase allows you to review a sample batch of meticulously annotated data, provide feedback, and confirm our 99% accuracy standard before we ramp up massive dataset production.
Who owns the datasets and IP after the annotation is complete?
You retain 100% exclusive ownership of all datasets and intellectual property. We provide full IP provenance and explicitly guarantee that your data is never repurposed, resold, or used to train internal models that might compete with your business.
Do we need to use our own internal platform, or do you provide tooling?
You can leverage our all-in-one Abaka Forge platform, which handles everything from collection and cleaning to annotation and training integration. It operates 50x faster via large-model automation, meaning you don't need to maintain costly internal annotation tooling.
Is there a minimum project size or volume requirement to work with you?
We support elastic scalability, accommodating everything from small, highly complex defensive coding evaluations (e.g., $15/eval) to massive autonomous driving lane projects ($3/km). We tailor our engagement to fit your precise needs, whether project-based or long-term embedded talent.