How do you price human data for LLMs and complex RLHF annotation?
Our pricing is highly transparent and tailored to the exact cognitive complexity required for your foundation models. For specialized tasks, we charge straight hourly rates based on the required scholar-network domain. For example, expert LLM Math and Coding annotation is explicitly priced at $18/hr, while a STEM Generalist is available at $12/hr. We also offer specialized tasks like dense captioning at $6/hr and image editing at $8/hr. This granular structure ensures you only pay for the specific expertise you need, avoiding bloated platform fees while securing a rigorous 99% accuracy standard.
What is the typical turnaround time for a custom dataset?
Speed and precision are central to our managed service. We typically complete scoping, taxonomy definition, and initial pilot delivery within the first 1 to 2 weeks. Once the pilot is approved by your engineering team, we rapidly scale our annotator pods. Our infrastructure supports a maximum throughput of 500 files per day per annotator, allowing us to condense traditional 4-month data collection cycles into just a few agile weeks of continuous, weekly deliveries.
Which modalities and data formats do you support?
We provide comprehensive modality coverage designed exclusively for state-of-the-art multimodal AI architectures. Through the Abaka Forge platform, we handle Text, LLM RLHF, Image, Video, 3D/4D Point Cloud, LiDAR + Camera fusion, and Audio data. We can deliver outputs in any standard format your ML pipelines require, including JSON, JSONL, Parquet, CSV, COCO, and proprietary API integrations. Our team ensures the final human data for LLMs is flawlessly formatted for immediate training without further preprocessing.
How do you ensure 99% accuracy on complex reasoning tasks?
We achieve exceptional quality through our exclusive scholar-network domains. Instead of relying on generic crowdsourcing, we recruit verified professionals, including mathematicians, scientists, and software engineers. Every piece of human data for LLMs passes through our multi-layer QA process, where senior domain experts rigorously audit the outputs against strict alignment guidelines. This methodology eliminates subtle hallucinations and logical errors, ensuring we maintain a baseline 99% accuracy on even the most intricate Chain-of-Thought prompts.
What security and compliance frameworks protect our data?
Data security and IP protection are the cornerstones of our operations. We maintain strict compliance with SOC 2, ISO 27001, GDPR, and CCPA frameworks. All annotation workflows occur within highly segregated secure pipelines governed by robust NDAs. We guarantee full IP provenance, resulting in an absolute 0% copyright risk on collected data. Most importantly, as a trustworthy data partner, we never build competing foundation models, meaning your proprietary data and algorithms remain entirely protected and exclusively yours at all times.
Can you handle multilingual RLHF and translation data?
Absolutely. We maintain a highly curated global network spanning more than 50 countries, enabling us to deliver native-level fluency across dozens of languages. Our experts generate high-fidelity multilingual human data for LLMs that perfectly captures local idioms, cultural context, and complex grammatical structures. Whether you are conducting global sentiment analysis, instruction tuning, or expansive multilingual QA, our specialized teams ensure your AI models deploy safely and accurately in any international market.
How does Abaka AI differ from generic crowdsourcing vendors?
Generic crowdsourcing vendors rely on anonymous, low-tier labor pools, resulting in severe quality decay when faced with complex AI alignment tasks. Abaka AI is fundamentally different. We are a trustworthy data partner for frontier AI that utilizes vetted scholar-grade intelligence. We deploy dedicated domain experts—from medical professionals to active software engineers—to craft highly technical human data for LLMs. Combined with our strict non-compete philosophy and SOC 2 secure pipelines, we deliver a level of safety, scale, and accuracy that standard vendors cannot match.
How are taxonomy adjustments and change requests handled?
We recognize that foundation model alignment is highly iterative. If your engineering team needs to adjust prompt distributions or modify the scoring rubric based on fresh benchmark results, our agile infrastructure adapts immediately. Your dedicated project manager facilitates these taxonomy adjustments during our regular weekly syncs. The revised guidelines are instantly propagated to your specialized annotator pods, ensuring the next batch of human data for LLMs perfectly reflects your model's newly evolved requirements.
Do you offer a pilot program before we commit to scaling?
Yes, every major engagement begins with a rigorous pilot phase. During the first two weeks, we collaborate closely with your AI team to define the taxonomy and deliver an initial batch of complex human data for LLMs. This allows you to evaluate our 99% accuracy standard and semantic fidelity directly in your training environment. We only scale the specialized annotator teams once you are completely satisfied that the pilot data perfectly aligns with your foundation model’s objectives.
Who owns the IP of the generated human data for LLMs?
You retain 100% exclusive ownership of all intellectual property generated during our engagement. We enforce strict IP provenance rules and operate under comprehensive NDAs, ensuring 0% copyright risk on the data we collect or annotate. Because Abaka AI is entirely self-funded and does not build internal models to compete with our clients, you can trust that your custom human data for LLMs will never be repurposed, resold, or utilized by any other organization.
Do we need to bring our own annotation tooling?
No internal tooling is required. We leverage our proprietary Abaka Forge platform, an all-in-one solution for data collection, cleaning, and annotation. The platform natively supports everything from complex RLHF text to 3D/4D Point Cloud rendering, accelerated by large-model automation. However, if your enterprise security policies mandate that the human data for LLMs be annotated directly within your proprietary infrastructure, our secure workforce can securely integrate into your internal tools via controlled VPN access.
Is there a minimum project size or volume commitment?
We are highly flexible and design our engagements to match your compute cycles. While we comfortably scale to support massive foundation model training runs—delivering thousands of files daily—we also support highly targeted, specialized projects, such as narrow adversarial red teaming or specific multilingual evaluations. We encourage you to Talk to an Expert to discuss your exact volume requirements, and we will structure a customized pipeline that aligns perfectly with your team's budget and timeline.
