Summary
Lamini is an enterprise LLM platform that enables businesses to train and deploy smaller, faster, and more accurate LLMs and agents using their proprietary data. It focuses on reducing hallucinations and offers secure deployment options, including on-premise and air-gapped environments. The platform provides tools for fine-tuning, memory RAG, and classification, catering to developers and enterprise teams.
Features7/13
See allMust Have
5 of 5
Conversational AI
API Access
Safety & Alignment Framework
Fine-Tuning & Custom Models
Enterprise Solutions
Other
2 of 8
Code Generation
Research & Publications
Image Generation
Multimodal AI
Security & Red Teaming
Synthetic Media Provenance
Threat Intelligence Reporting
Global Affairs & Policy
PricingUsage-based
See allFree
- Upto 10 projects
- Customizable dashboard
- Upto 50 tasks
- Upto 1 GB storage
Starter
- Upto 10 projects
- Customizable dashboard
- Upto 50 tasks
- Upto 1 GB storage
- Unlimited proofings
Pro
- Upto 10 projects
- Customizable dashboard
- Upto 50 tasks
- Upto 1 GB storage
- Unlimited proofings
- Unlimited custom fields
- Unlimited milestones
- Unlimited timeline
On-demand Inference
- Pay as you go
- Access to top open source models like Llama 3.1, Mistral v0.3, and Phi 3
- Runs on Lamini’s optimized compute platform, generating state-of-the-art MoME models
On-demand Tuning
- Pay as you go
- Scale number of steps based on your data
- Linear multiplier - burst tuning across multiple GPUs or nodes for faster performance
Reserved
- Run on reserved GPUs from Lamini
- Unlimited tuning and inference
- Unmatched inference throughput
- Full evaluation suite
- Enterprise support
Self-managed
- Run Lamini in your own secure environment (VPC, on-prem, air-gapped)
- Run Lamini on your own GPUs
- No internet access needed
- Pay per software license
- Full evaluation suite
- Access to world-class ML experts
- Enterprise support
Rationale
Lamini is an enterprise LLM platform that directly aligns with the OpenAI Platform concept. It offers fine-tuning capabilities for custom models, API access for integration, and explicitly targets enterprise solutions with features like secure deployment (on-premise, VPC, air-gapped) and advanced security. The platform aims to reduce hallucinations and improve accuracy, which aligns with safety and alignment. While not explicitly called 'conversational AI', its use cases like 'Factual reasoning chatbots' and 'Customer Support Agent' imply conversational AI capabilities. It also mentions 'Code Helper' for code generation and refers to research papers and guides, indicating a focus on research and publications.
