How much does it cost to hire an AI model training data vendor?
Pricing depends heavily on the complexity and modality of the data. At Abaka AI, we offer transparent, highly competitive rates based on required expertise. For example, general STEM QA and dense captioning typically start around $6/hr, while advanced LLM Math and Coding tasks are priced at $18/hr. For specialized automotive needs, road lane annotation runs $3/km, and advanced Red Teaming evaluations cost $8/eval. All pricing is straightforward with zero hidden platform fees, ensuring you only pay for highly accurate, usable data.
How fast can you scale up an annotation team for our project?
We move at the speed of frontier AI. Through our global network of over 1M vertically specialized annotators, we can typically scope your requirements, assemble a dedicated capture pod or labeling team, and begin pilot evaluations within Day 0 to 3. By Week 2, we completely elasticize the workforce for massive throughput, allowing individual experts to process up to 500 files per day. This rapid scaling drastically reduces your preprocessing time.
What modalities and file formats do you support?
Our proprietary Abaka Forge platform supports natively all major data modalities required for frontier models. We process multi-lingual text, complex interleaved images, video spatial tracking, 3D/4D point clouds, LiDAR + camera sensor fusion, and complex audio streams. Output formats are fully customizable to fit your ML pipeline, including JSON, Parquet, COCO, JSONL, PCD, and custom API endpoints, ensuring seamless integration into your current training workflows.
How do you guarantee high accuracy in complex data labeling?
Unlike vendors that rely entirely on anonymous crowd workers, we curate a highly specialized, scholar-level network of PhDs, mathematicians, and certified experts. Every dataset passes through a stringent, multi-layer QA protocol managed by senior reviewers. We implement continuous Model-as-Judge frameworks and human evaluation protocols, ultimately achieving and maintaining a strict 99% accuracy rate across highly nuanced tasks like Lean4 mathematics and intricate RLHF logic.
Is our intellectual property and proprietary data secure with you?
Absolutely. Security and IP protection are the foundational pillars of our service. Our operations are fully SOC 2 and ISO 27001 certified, and we ensure strict compliance with global standards like GDPR and CCPA. Every annotator operates under tight NDAs, and we utilize segregated, secure data pipelines to completely eliminate data leakage. We guarantee 100% provenance and 0% copyright risk on all collected and annotated data.
Can you provide multi-lingual data sourcing and RLHF annotation?
Yes. We source talent and collect real-world data from over 50 countries, allowing us to build extensive multi-lingual datasets with localized nuance. Whether you need sentiment analysis, translation pre-training data, or culturally aligned multi-turn dialogue for conversational agents, our native-speaking experts ensure your foundational models generalize perfectly across global languages without localized bias or factual hallucinations.
How does Abaka AI differ from other AI model training data vendors?
The core difference is absolute trust and deep expertise. We are 100% self-funded and profitable, meaning we face no VC pressure to pivot or acquire. More importantly, we never build proprietary models that compete with our clients. Your data is exclusively yours. Combine this with our 50x faster Abaka Forge large-model automation and an elite network of scholar-level annotators, and you get a partner focused purely on delivering unparalleled data fidelity.
How do you handle changes to labeling guidelines mid-project?
Agility is built into our operational model. We understand that as your foundation model evolves, your data requirements often shift. You are partnered with dedicated embedded engineering teams who monitor continuous feedback loops. If guidelines require updating, we instantly pause workflows, run targeted re-calibration pilots on Abaka Forge, and update the multi-layer QA standards before seamlessly resuming mass production—ensuring zero waste in your budget.
Can we run a pilot before committing to large-scale data volume?
Yes, we strongly encourage a rigorous pilot phase for every new engagement. During Week 1, we align a specialized subset of our domain experts to your specific instructions. We annotate a diverse sample batch to test edge cases, refine subjective guidelines, and calibrate our QA reviewers. We only scale to full production once you validate the pilot’s output, ensuring the data perfectly matches your algorithmic expectations.
Who owns the data and models once the project is completed?
You maintain 100% exclusive ownership of every data point, annotation, and model evaluation we produce for you. We operate strictly as a service and platform provider. Your data is never repurposed, resold, or used to train external models. With our full IP provenance tracking, you can deploy your AI models with total legal confidence and zero competitive risk from your vendor.
Do we have to use your platform, or can you work within our tooling?
While our Abaka Forge platform is highly recommended due to its 50x faster large-model automation and integrated SOC 2 security, we are fully adaptable. Our embedded talent can securely access and operate within your proprietary, in-house labeling tools or third-party platforms if required. We aim to act as a seamless extension of your AI engineering team, strictly conforming to your preferred technological ecosystem.
Do you have minimum data volume requirements for enterprise engagements?
We support a highly elastic engagement model, allowing us to adapt from highly targeted boutique projects to massive, multi-petabyte pre-training data collections. Whether you need a small batch of $15/eval defensive coding evaluations or require a dedicated, long-term embedded team for continuous RLHF, we structure our workflows to meet your exact scale and budget without forcing restrictive volume floors.
