How much does your data annotation company charge for specialized AI tasks?
Abaka AI operates on a highly transparent, specialized pricing model based on the complexity of the task and the domain expertise required, completely avoiding hidden fees. For example, our LLM Math and Coding evaluation services are priced at $18/hr, leveraging certified software engineers and mathematicians. General STEM QA tasks are handled at $12/hr, while advanced image editing is $8/hr. For autonomous driving datasets, we offer precise road lane annotation at just $3/km. Furthermore, processing credits on the Abaka Forge platform are available for $0.20 USD each, providing extremely cost-effective scaling for massive foundational model runs.
How fast can you deliver fully annotated datasets for our model training?
Speed is critical for frontier AI development, which is why we integrate large-model automation into the Abaka Forge platform to accelerate workflows by up to 50x. Once a pilot is successfully integrated—typically within the first three days—we immediately ramp up our global workforce. Because our elastic infrastructure allows individual annotators to process up to 500 files per day securely, we can deliver massive, high-quality training batches in a matter of weeks rather than months. We ensure your machine learning engineers never sit idle waiting for clean data.
What data modalities and output formats do you natively support?
We natively support an extensive range of critical AI modalities through the Abaka Forge platform, ensuring complete coverage for diverse model architectures. Our teams expertly handle multi-turn Text RLHF, complex Image and Video spatial reasoning, detailed Audio transcription, and highly advanced 3D/4D Point Cloud and LiDAR-camera sensor fusion. Whether you need JSON and Parquet for language models, COCO and YOLO for computer vision, or custom ROS bags for embodied robotics, we export data in perfectly structured formats ready for immediate ingestion into your specialized machine learning pipelines.
How do you guarantee high accuracy across complex annotation workflows?
Achieving flawless precision is our core mandate. We guarantee a 99% accuracy rate by exclusively deploying highly educated, domain-specific professionals from our scholar-network, completely bypassing unreliable generic crowdsourcing. For complex tasks like chemical analysis or defensive coding, we utilize a strict multi-layer quality assurance framework. This includes objective benchmarking, advanced model-as-a-judge automated checks within Abaka Forge, and rigorous manual reviews by senior subject matter experts. This redundant, uncompromising QA process ensures that every single data point contributing to your frontier model is factually correct and perfectly aligned.
What security and compliance measures protect our proprietary training data?
As a trusted data partner for Tier-1 enterprises and defense agencies, we provide fortress-level security protocols. All data processing occurs strictly within our fully segregated secure pipelines, preventing any unauthorized access or cross-contamination. Abaka AI is fully compliant with SOC 2, ISO 27001, GDPR, and CCPA standards. We enforce rigorous NDAs across our entire global workforce and guarantee 0% copyright risk on all collected and annotated data. You retain absolute control over your intellectual property, ensuring that your customized model architectures remain highly confidential and securely protected at all times.
Can your annotators support multilingual models and specific regional dialects?
Absolutely. Training globally capable foundational models requires deep linguistic and cultural nuance. Our meticulously vetted network of over one million annotators spans more than 50 countries, granting you direct access to true native speakers across hundreds of languages and localized dialects. This vast global presence enables us to deliver highly accurate multilingual text translation, localized sentiment analysis, and culturally sensitive conversational RLHF. By capturing precise linguistic inflections and regional context, we ensure your natural language processing models perform flawlessly and safely across diverse, worldwide consumer markets.
Why should we choose Abaka AI over other data labeling platforms?
Unlike traditional venture-backed labeling platforms that rely on generic click-workers and aggressive sales tactics, Abaka AI is a self-funded, highly profitable enterprise founded in 2019. We differentiate ourselves by deploying specialized scholar-networks tailored for frontier AI, ensuring 99% accuracy on complex tasks like Lean4 math and spatial reasoning. Crucially, we operate with maximum integrity: we never build foundational models that compete with our clients, and we never repurpose or resell your proprietary data. When you partner with us, you secure a reliable, long-term ally dedicated entirely to your success.
How do you handle sudden shifts in our AI model's annotation guidelines?
Agility is built directly into our operational model. We understand that as AI models evolve—especially during dynamic RLHF and agentic training—your annotation requirements will inevitably shift. We host mandatory weekly review and calibration syncs with your engineering team to discuss edge cases and immediately update project guidelines. Our flexible Abaka Forge platform allows us to seamlessly push new instructions to our specialized workforce in real-time. This ensures that any sudden pivot in your model’s architecture is instantly mirrored by our annotators without causing disruptive delays in data delivery.
Do you offer a pilot program before we commit to full-scale production?
Yes, every new engagement begins with a highly focused, rapid pilot program. During the crucial Day 0–3 phase, we conduct a deep-dive consultation to align on your specific modalities and strictly define data provenance. We then configure Abaka Forge and deploy a select group of specialized annotators to process an initial subset of your data. This pilot guarantees that our 99% accuracy benchmark and output formats exactly meet your engineering team's stringent requirements before we authorize the elastic scaling of your customized, high-volume production pipeline.
Who owns the rights to the data annotated by your team?
You retain 100% exclusive ownership of all data processed, collected, and annotated by Abaka AI. We act strictly as a secure, third-party processing partner. Your proprietary datasets, customized guidelines, and intellectual property are never resold, shared, or repurposed to train internal models or assist other clients. Because we offer a strict guarantee of 0% copyright risk on any organically collected data, you can aggressively scale your foundational models with complete confidence, knowing your intellectual property remains fully protected and entirely under your corporate control.
Do we need to use our own software, or do you provide annotation tools?
You do not need to build or license external software. We provide full access to Abaka Forge, our proprietary, all-in-one data platform designed specifically for frontier AI. Abaka Forge seamlessly handles end-to-end data collection, rigorous cleaning, intricate annotation, and model evaluation within a single, unified interface. Powered by advanced large-model automation, it accelerates workflows by up to 50x across all modalities, including Text RLHF, Video, and 3D Point Clouds. This robust internal tooling drastically reduces your technical overhead while maximizing dataset quality and delivery speed.
Is there a minimum project size required to partner with your company?
We are structurally designed to support the dynamic, unpredictable lifecycles of modern AI development, which means we highly prioritize elastic scalability over rigid minimums. Whether you require a hyper-targeted pilot using specialized healthcare annotators for a brief medical imaging run, or continuous high-throughput data processing for a global autonomous driving fleet, we rapidly adapt to your needs. Our flexible, consumption-based pricing model allows your AI lab to start with a focused, small-scale dataset and scale seamlessly to millions of annotations the moment your foundational model requires massive data volume.