TrueFoundry is a cloud-native PaaS that enables enterprise teams to experiment as well as productionize advanced ML and LLM workflows on their own cloud/on-prem infra with full data privacy and security, 100% reliability and scalability and cost optimization - allowing them to launch AI applications to production 90% faster than other teams
TrueFoundry is open-ended, API Driven and integrates with the internal systems, deploys on a company's internal infrastructure and ensures complete Data Privacy and DevSecOps practices.
Visit www.truefoundry.com to learn more.
Product Description
TrueFoundry's LLMOps platform is a comprehensive solution designed to streamline the deployment, management, and scaling of large language model applications within enterprise environments. It offers a unified interface that integrates seamlessly with various LLM providers, ensuring efficient operations across cloud and on-premises infrastructures.
Key Features and Functionality:
- Model Serving & Inference: Deploy any open-source LLM using pre-configured, performance-optimized setups. Integrate effortlessly with platforms like Hugging Face and private registries. Utilize advanced model servers such as vLLM and SGLang for low-latency, high-throughput inference. Benefit from GPU autoscaling, automatic shutdown, and intelligent resource provisioning.
- Efficient Fine-Tuning: Support both no-code and full-code fine-tuning on custom datasets. Implement LoRA and QLoRA for efficient low-rank adaptation. Resume training seamlessly with checkpointing support. Deploy fine-tuned models with a single click using top-tier model servers. Automate training pipelines with built-in experiment tracking. Leverage distributed training for faster, large-scale model optimization.
- Secure and Scalable AI Gateway: Provide a unified API layer to manage models across various providers like OpenAI, LLaMA, and Gemini. Implement quota management and access control to enforce secure model usage. Access real-time metrics for usage, cost, and performance. Ensure reliability with intelligent fallback mechanisms and automatic retries.
- Structured Prompt Workflows: Facilitate version-controlled prompt engineering. Conduct A/B testing across models to optimize performance. Maintain full traceability of prompt changes.
- Tracing & Guardrails: Capture comprehensive traces of prompts, responses, token usage, and latency. Monitor performance, completion rates, and anomalies. Integrate guardrails for PII detection and content moderation.
- One-Click RAG Deployment: Deploy all Retrieval-Augmented Generation components, including VectorDB, embedding models, frontend, and backend, with a single click. Optimize storage, retrieval, and query processing through configurable infrastructure. Handle expanding document bases with cloud-native scalability.
- AI Agent Lifecycle Management: Run and scale agents across any framework, including LangChain, AutoGen, CrewAI, and custom agents. Orchestrate agents with built-in monitoring. Support multi-agent orchestration for autonomous task execution.
- MCP Server Integration: Securely connect LLMs to tools like Slack, GitHub, and Confluence using the MCP protocol. Deploy MCP Servers in various environments, including VPC, on-premises, or air-gapped setups. Enable prompt-native tool use without wrappers. Govern access with RBAC, OAuth2, and maintain observability.
Primary Value and Problem Solved:
TrueFoundry addresses the complexities of deploying and managing LLM applications at scale by offering an integrated platform that simplifies the entire lifecycle—from model serving and fine-tuning to monitoring and governance. By providing tools for efficient resource management, secure API access, and comprehensive observability, TrueFoundry enables organizations to accelerate development cycles, reduce infrastructure costs, and achieve faster time-to-value. This empowers data scientists and developers to focus on building and optimizing AI applications without the overhead of managing complex infrastructure.
