Democratizing AI Training
DeTrainAI decentralizes large-scale model training, building a transparent and cost-efficient economic ecosystem where compute, data, and expertise flow openly — an alternative to closed, centralized AI.
BENEFITS
Why Choose Us?
Why Choose Us?
Catering to all AI needs
Decentralized Training Power
Tap into a global network of contributors, not a single closed system.
Decentralized Training Power
Tap into a global network of contributors, not a single closed system.
Decentralized Training Power
Tap into a global network of contributors, not a single closed system.
Cost Efficiency
Lower training costs compared to traditional centralized AI labs.
Cost Efficiency
Lower training costs compared to traditional centralized AI labs.
Cost Efficiency
Lower training costs compared to traditional centralized AI labs.
Economic Ecosystem
A transparent model where compute, data, and expertise sustain each other.
Economic Ecosystem
A transparent model where compute, data, and expertise sustain each other.
Economic Ecosystem
A transparent model where compute, data, and expertise sustain each other.
Trust & Security
Staking and slashing mechanisms ensure integrity in every contribution.
Trust & Security
Staking and slashing mechanisms ensure integrity in every contribution.
Trust & Security
Staking and slashing mechanisms ensure integrity in every contribution.
Scalable & Flexible
Run multiple fine-tuning and validation tasks in parallel
Scalable & Flexible
Run multiple fine-tuning and validation tasks in parallel
Scalable & Flexible
Run multiple fine-tuning and validation tasks in parallel
Enterprise Ready
Custom LLM training with revenue shared across nodes.
Enterprise Ready
Custom LLM training with revenue shared across nodes.
Enterprise Ready
Custom LLM training with revenue shared across nodes.
SERVICES
Building AI, the decentralized way
Decentralized AI solutions — from custom LLM training to enterprise integration, powered by a transparent economic ecosystem.
Trade
Language
Medical
Legal
Custom LLM Training
Fine-tuned models built on your data through a decentralized network
Trade
Language
Medical
Legal
Custom LLM Training
Fine-tuned models built on your data through a decentralized network
Trade
Language
Medical
Legal
Custom LLM Training
Fine-tuned models built on your data through a decentralized network
Decentralized Training Network
Harness global compute and validators for scalable AI training.
Decentralized Training Network
Harness global compute and validators for scalable AI training.
Decentralized Training Network
Harness global compute and validators for scalable AI training.
Independent Validators
Validate
Transparent Metrics
Incentive Alignment
Enterprise Standards
Validation & Quality Assurance
Independent nodes ensure accuracy, reliability, and trust.
Independent Validators
Validate
Transparent Metrics
Incentive Alignment
Enterprise Standards
Validation & Quality Assurance
Independent nodes ensure accuracy, reliability, and trust.
Independent Validators
Validate
Transparent Metrics
Incentive Alignment
Enterprise Standards
Validation & Quality Assurance
Independent nodes ensure accuracy, reliability, and trust.
Code
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2
3
4
5
Economic Ecosystem
Revenue flows transparently across the network of training nodes.
Code
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2
3
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5
Economic Ecosystem
Revenue flows transparently across the network of training nodes.
Code
1
2
3
4
5
Economic Ecosystem
Revenue flows transparently across the network of training nodes.
Enterprise Integration
Seamless API access and deployment into existing business systems.
Enterprise Integration
Seamless API access and deployment into existing business systems.
Enterprise Integration
Seamless API access and deployment into existing business systems.
FEATURES
Powering the Future of Decentralized AI
Core features that make DeTrainAI secure, scalable, and enterprise-ready.
Decentralized Training
Harness a global network of nodes instead of centralized labs.
Decentralized Training
Harness a global network of nodes instead of centralized labs.
Decentralized Training
Harness a global network of nodes instead of centralized labs.
Enterprise Customization
Train and deploy models on proprietary data at scale.
Enterprise Customization
Train and deploy models on proprietary data at scale.
Enterprise Customization
Train and deploy models on proprietary data at scale.
Independent Validation
Quality guaranteed by validator nodes with reputation scoring.
Independent Validation
Quality guaranteed by validator nodes with reputation scoring.
Independent Validation
Quality guaranteed by validator nodes with reputation scoring.
Transparent Economy
A fair token-driven system for sustainable AI development.
Transparent Economy
A fair token-driven system for sustainable AI development.
Transparent Economy
A fair token-driven system for sustainable AI development.
Task Board Management
Coordinate multiple training and fine-tuning jobs in parallel.
Task Board Management
Coordinate multiple training and fine-tuning jobs in parallel.
Task Board Management
Coordinate multiple training and fine-tuning jobs in parallel.
Staking & Security
Token-based staking ensures trust, with slashing against bad actors.
Staking & Security
Token-based staking ensures trust, with slashing against bad actors.
Staking & Security
Token-based staking ensures trust, with slashing against bad actors.
PROCESS
How DeTrainAI Works
A step-by-step journey from requirement to deployment, powered by decentralization and trust.
STEP 1
STEP 2
STEP 3
STEP 4
STEP 5
STEP 6
STEP 7
01
Requirement
Organizations define their AI goals — from fine-tuning domain-specific LLMs to building custom models — and submit them as requests. This sets the foundation for every training job.
STEP 1
STEP 2
STEP 3
STEP 4
STEP 5
STEP 6
STEP 7
01
Requirement
Organizations define their AI goals — from fine-tuning domain-specific LLMs to building custom models — and submit them as requests. This sets the foundation for every training job.
STEP 1
STEP 2
STEP 3
STEP 4
STEP 5
STEP 6
STEP 7
01
Requirement
Organizations define their AI goals — from fine-tuning domain-specific LLMs to building custom models — and submit them as requests. This sets the foundation for every training job.
FAQ'S
Frequently Asked Questions
Find quick answers to the most common support questions
Still Have Questions?
Still have questions? Feel free to get in touch with us today!
Why combine centralized task design with decentralized execution?
This hybrid model ensures tasks are well-structured and high quality (avoiding chaos from full decentralization) while still benefiting from the scale, cost savings, and fairness of a decentralized network.
How does DeTrainAI prevent bad actors from gaming the system?
Nodes must stake $DTRN tokens to participate. If they submit poor or malicious work, their stake is slashed, aligning incentives toward honest contributions.
What makes DeTrainAI more cost-efficient than cloud-based AI training?
Instead of renting expensive centralized compute from a single provider, DeTrainAI distributes workloads across global nodes, cutting costs while improving redundancy and scalability.
Can enterprises keep their proprietary data secure during training?
Yes — training tasks are split and distributed in a way that ensures data privacy. Enterprises can choose to run sensitive portions on their own secure nodes if required.
How is validator reputation tracked?
Validators earn credibility through accurate performance over time. A scoring system ranks validators, giving enterprises confidence that only the most reliable nodes validate their outputs.
What happens if demand for training spikes?
The task board automatically scales by assigning jobs to available trainer nodes worldwide, ensuring workloads are distributed efficiently without bottlenecks.
FAQ'S
Frequently Asked Questions
Find quick answers to the most common support questions
Still Have Questions?
Still have questions? Feel free to get in touch with us today!
Why combine centralized task design with decentralized execution?
This hybrid model ensures tasks are well-structured and high quality (avoiding chaos from full decentralization) while still benefiting from the scale, cost savings, and fairness of a decentralized network.
How does DeTrainAI prevent bad actors from gaming the system?
Nodes must stake $DTRN tokens to participate. If they submit poor or malicious work, their stake is slashed, aligning incentives toward honest contributions.
What makes DeTrainAI more cost-efficient than cloud-based AI training?
Instead of renting expensive centralized compute from a single provider, DeTrainAI distributes workloads across global nodes, cutting costs while improving redundancy and scalability.
Can enterprises keep their proprietary data secure during training?
Yes — training tasks are split and distributed in a way that ensures data privacy. Enterprises can choose to run sensitive portions on their own secure nodes if required.
How is validator reputation tracked?
Validators earn credibility through accurate performance over time. A scoring system ranks validators, giving enterprises confidence that only the most reliable nodes validate their outputs.
What happens if demand for training spikes?
The task board automatically scales by assigning jobs to available trainer nodes worldwide, ensuring workloads are distributed efficiently without bottlenecks.
FAQ'S
Frequently Asked Questions
Find quick answers to the most common support questions
Still Have Questions?
Still have questions? Feel free to get in touch with us today!
Why combine centralized task design with decentralized execution?
How does DeTrainAI prevent bad actors from gaming the system?
What makes DeTrainAI more cost-efficient than cloud-based AI training?
Can enterprises keep their proprietary data secure during training?
What industries benefit the most?
How is validator reputation tracked?
Validators earn credibility through accurate performance over time. A scoring system ranks validators, giving enterprises confidence that only the most reliable nodes validate their outputs.
What happens if demand for training spikes?
The task board automatically scales by assigning jobs to available trainer nodes worldwide, ensuring workloads are distributed efficiently without bottlenecks.
COMPARISON
Why Choose Us Over Others
Why Choose Us Over Others
See how we compare against others in performance, growth
See how we compare against others in performance, growth
Open and global access for contributors and enterprises.
Lower training costs through distributed compute.
Community-driven governance with clear enterprise focus.
Independent validator nodes ensure quality and trust.
Transparent token economy with fair revenue sharing.
Others
Closed and controlled by a few corporations.
High compute and infrastructure costs.
Validation is internal, with limited transparency.
Enterprises pay for access but lack flexibility.
Profits remain within the company only.
