Find Failure
Continuously identify where models struggle in real-world deployment instead of relying on assumptions.
Smarter data, smarter AI.
Most companies sell you data.We make your models better.
The Thoth Loop
Prescribe Data
Determine exactly which experiences and annotations are needed to improve the next model iteration.
Deliver Data
Route the right tasks to the right experts, producing high-quality training data at scale.
Improve Model
The models you deploy keep learning — from every interaction.
The LoopWhy the loop
The market sells data.
Why the loop
matters
A self-reinforcing data flywheel that continuously improves model performance.
- Find Failure
- Prescribe Data
- Deliver Data
- Improve Model
Smarter data.
Smarter models.
The Industry Today
- Collect
- Label Everything
- Hope it Improves
The Thoth Loop
- Find Failure
- Prescribe Data
- Deliver Data
- Improve Model
The market sells data.
The goal was always a better model.
Intelligence should not exist as a collection of isolated models or disconnected workflows. It should operate as a continuous system that observes, learns, adapts, and improves over time.
Products
Explore
Embodied AI & Robotics
Capture real-world experience and transform every deployment into smarter robotic behavior.
Explore
LLM Reliability
Improve AI reliability through intelligent routing, human verification, and continuous learning.
Explore
The Annotation Platform
Build expert-led training data that continuously improves quality, consistency, and model performance.
The timing isn't an accident.
Physical AI
is scaling.
Robots need real-world data to learn what the internet doesn't have.
$18.6B
Invested in Robotics in 2024
↗ 31% YoY
2.4x
More deployment of AI-enabled robots (2023–2024)
Reliability is now
the buying criterion.
Enterprises care more about accuracy, consistency, and trust than model size.
78%
reliability priority in 2026*
78%
of enterprise AI initiatives cite reliability as the top priority in 2026*
57%
Of production LLM outputs require human review today*
4.3x
Higher cost of errors than model improvements*
1 in 2
Enterprises have delayed AI projects due to reliability concerns*
*Sources: Deloitte 2026 AI Outlook, Gartner, Stanford AI Index 2025
Data is the
new bottleneck.
The best models are limited by the quality and relevance of training data.
>80%
Of AI projects are limited by training data quality or availability*
10x
More high-quality data needed for frontier AI models (MoE era)*
*Sources: McKinsey, Scale AI, Stanford AI Index 2025
The bottleneck has moved from compute to the right data.
— The Thoth Thesis
Continuous learning
compounds advantage.
Every interaction, every failure, every fix makes the system better.
2–5x
Performance improvement from continuous learning loops vs static training*
30–50%
Lower total cost of ownership with continuous learning systems*
*Sources: BCG, Windsurf AI, Stanford AI Index 2025
CapabilitiesBuilt by people who've
Built by people who've
done this before.
Annotation workforce
1,000+ experts across robotics, vision, multimodal reasoning and RLHF.
- Programmers
- Physicists
- Medical experts
- Designers
- Writers
- Artists
- Audio/video pros
- Industry specialists
Silicon Valley
A research and engineering team working alongside your model roadmap.
Robotics data
Real operators, live capture — teleoperation, demonstration and failure recovery at scale.