Predibase offers an enterprise platform designed to monitor, govern, and rewind actions performed by AI agents. This system provides a single source of truth for all agent activity, enabling early risk identification through comprehensive observation. Users can apply granular, policy-based controls to prevent unauthorized actions and utilize an instant undo feature to roll back unintended outcomes safely.
Funding
$12.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
FFVGFounders
Product
Problem
Deploying and customizing large language models (LLMs) can be prohibitively expensive and complex, requiring significant infrastructure and specialized expertise. Many organizations struggle to achieve the desired performance and cost-efficiency when adapting general-purpose LLMs to specific tasks.
Solution
Predibase offers a platform for fine-tuning and deploying small language models (SLMs) that delivers performance comparable to larger models at a fraction of the cost. The platform provides tools for efficient fine-tuning, including techniques like quantization and low-rank adaptation (LoRA), enabling users to customize models on their own cloud infrastructure or within Predibase's environment. Predibase's serving infrastructure, powered by Turbo LoRA and LoRAX, allows for cost-effective serving of numerous fine-tuned adapters on a single GPU, optimizing resource utilization and reducing operational expenses.
Target Audience
The primary target audience includes organizations seeking to leverage the power of LLMs for specific use cases while minimizing costs and maintaining control over their data and models, including those in AI, and Web3.
Features
- Support for a wide range of open-source LLMs, including Llama 3, Phi-3, and Mistral.
- Optimized fine-tuning system with automated optimizations like quantization, LoRA, and memory-efficient distributed training.
- Scalable serving infrastructure powered by Turbo LoRA and LoRAX for cost-effective deployment of multiple fine-tuned models.
- LoRA Exchange (LoRAX) architecture enabling the serving of thousands of fine-tuned LLMs on a single GPU.
- Option to deploy models in Predibase's cloud or a user's own virtual private cloud (VPC).
- Tools for classification, information extraction, customer sentiment analysis, customer support automation, code generation, and named entity recognition.
- SOC-2 compliance for secure customization of open-source models on user data.