Mind Lab - Turn enterprise expertise into proprietary industry model capabilities
Mind Lab is an industry-focused platform for model training and inference. It provides end-to-end services including benchmarking, custom training data development, model post-training, inference, and deployment. The platform serves pharmaceutical, financial, public sector, and gaming organizations. It supports both small task-focused models and large frontier models while reducing training compute costs significantly.
- AI DevTools
- Model Training
- Healthcare
- Finance
- Gaming
- Fine-tuning
- Deployment
- Model Evaluation
- Self-hosted
- Enterprise
- Multi-language
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Capabilities
Industry benchmark building
Creates dedicated industry-specific model training benchmarks. It maps enterprise workflows, expert practices and historical cases, then defines scoring logic and acceptance standards.
Custom training data development
Builds tailored training datasets aligned to vertical enterprise use cases. It incorporates verified expert traces, industry task rules and real-world scenario edge cases.
Vertical model post-training
Performs post-training to align base models with specific industry requirements. It uses LoRA, shared bases and distributed optimization to reduce total training compute costs.
Model inference and deployment
Delivers end-to-end model inference and deployment services. It supports private, VPC and hybrid workspace deployment configurations for enterprise environments.
Multi-mode training access
Provides three distinct working modes for different team needs. It offers expert-led full service, automated platform execution, and self-directed infrastructure access for training.
Pricing
Pricing is available via direct contact, with specialist training starting at $1000. Teams can select the working mode that matches their existing resources and operational needs.
Free trial: No
All pricing details, custom quota terms and full service scope are confirmed through direct consultation with the Mind Lab team after submitting an inquiry.
Use cases
Pharmaceutical industry model training
For pharmaceutical teams needing domain-specific AI models, the platform trains models for literature retrieval, evidence review, AI drug discovery and medical data governance using industry-specific benchmarks and expert traces.
Financial industry custom model build
For financial organizations seeking proprietary AI capabilities, the platform develops post-trained models aligned to vertical financial tasks, deployed in private workspaces to meet internal compliance requirements.
Self-directed research model training
For algorithm and research teams that already have custom models and datasets, the platform provides large-scale cluster infrastructure and distributed training resources to run custom loss functions and training loops.
Who it is for
Pharmaceutical and healthcare organizations needing domain-aligned AI models
Financial companies requiring proprietary vertical AI capabilities
Product and business teams without dedicated AI research resources
Algorithm and research teams needing scalable training infrastructure
FAQ
What base models are supported for training?
The platform supports a range of base models including GLM, DeepSeek, Kimi, Qwen and MiniMax, covering both small task-focused models and large frontier models.
What deployment options are available?
Supported deployment options include cloud, private, VPC and hybrid workspace setups, selected based on the enterprise's specific security and operational requirements.
How much can training compute costs be reduced?
The platform reduces training compute costs by 90% compared to standard approaches using LoRA, shared bases and distributed optimization techniques.
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