Capture expertise |
from engineers who ship.
Not labels. Not annotations. The actual thought process of senior developers — with eval attribution that proves ROI.
Quality doesn't scale linearly with quantity.
Scale AI built a gig worker army. They labeled fast. But gig workers don't understand code. They follow rubrics. Rubrics can't capture reasoning.
"The marginal buyer of data is increasingly sophisticated about vendor risk. Fragmentation is the durable equilibrium."
— State of Data, Jan 2026
Prove your training data works.
Scale gives you a CSV and says "good luck." We give you a dashboard that shows exactly how our data moved your evals. Data → Train → Eval → Iterate.
Close the loop from data to eval.
Purpose-built for LLM training
Specialized interfaces for code and text, designed for speed and accuracy.
Supported task types
Purpose-built for LLM data
Our labeling platform handles both code and non-code data with specialized interfaces for each task type.
Explain the difference between supervised and unsupervised learning in machine learning. Include examples.
Supervised Learning uses labeled data to train models. The algorithm learns to map inputs to known outputs.
Examples: spam detection, image classification...
Unsupervised Learning finds patterns in unlabeled data without predefined outputs.
Examples: customer segmentation, anomaly detection...
Supported data types
Text & conversational data labeling
Beyond code, we also support general-purpose LLM training with high-quality human feedback for text generation, Q&A, summarization, and more.
- Response quality comparison
- Tone & style evaluation
- Factual accuracy checks
- Question-answer pairs
- Document summarization
- Multi-turn conversations
- Harmful content detection
- Bias identification
- Refusal scenario training
Engineers who ship, not gig workers
Ex-Nubank, Ex-Rappi, Ex-MercadoLibre. LatAm's best engineers who've shipped production code, not contractors following rubrics.
Evals decay. Data must flow.
"Evals need to be dynamic and constantly changing every week." We deliver fresh data continuously, not quarterly batches.
We're not a vendor. We're a data partner.
Watch your evals climb
Real-time visibility into how our training data moves your benchmarks. Track HumanEval, MBPP, safety scores, and custom evals week over week.
Benchmark Trajectory
Model performance over training cycles
Scale sells data.
We sell eval improvement.
See the difference between commodity labels and engineering-grade reasoning traces.
 | Scale AI | Surge AI | |
|---|---|---|---|
| What you get | Reasoning + Eval proof | Labels | Labels |
| Delivery model | "Here's your eval delta" | "Here's a CSV" | "Here's a CSV" |
| Feedback | Weekly iteration calls | None | Limited |
| When evals drop | We already pivoted | Buy more data | Buy more data |
| ROI visibility | Dashboard | Hope | Hope |
| Workforce | 30K elite engineers | 500K gig workers | 100K gig workers |
| They understand | Code | Rubrics | Rubrics |
| Turnover | <5%/year | Weekly | Monthly |
Ready to close
the loop?
See your eval deltas within 2 weeks. Real ROI, not just data dumps.
Prefer email?
llm@amplifyit.io"The last mile between your model and production"