About Tensorlake
Tensorlake is an enterprise-grade platform designed to serve as the foundational engine for agentic applications. It provides a comprehensive infrastructure that allows developers to focus on application logic rather than the underlying complexities of durable execution, document ingestion, and multi-cloud compute management. By integrating these critical components into a single environment, the platform facilitates the deployment of production-ready agents that can handle complex, long-running tasks within an enterprise setting. The system's architecture is built to ensure that progress is never lost, even when individual components or external API calls fail, allowing agents to resume exactly where they left off.
At the heart of the platform is a serverless agent runtime that utilizes a Python-native interface for defining workflows. Developers can use simple decorators to define functions, manage parallel execution across thousands of nodes, and even attach high-performance H100 GPUs to specific steps in a workflow. This flexibility is supported by a built-in 1TB persistence layer, which eliminates the need for managing external message brokers like Kafka or Redis when ingesting massive datasets. The platform also features "No-SQL parallelism," enabling data-warehouse levels of concurrency directly through Python commands like .map(), which fan out execution tasks instantly.
For organizations dealing with complex data sources, Tensorlake offers advanced Document AI capabilities. Unlike standard OCR tools, its ingestion pipeline is layout-aware, meaning it understands the natural reading order of documents with complex structures, such as tables, charts, and mathematical equations. It can extract structured data guided by JSON schemas and provide bounding boxes for precise citations, which significantly reduces the risk of LLM hallucinations caused by mangled input data. Every agent session is further protected by isolated code sandboxes, ensuring that any code generated by an LLM is executed safely without the risk of leaking data across sessions or compromising system integrity.
Tensorlake is particularly well-suited for enterprise developers and data engineers who need to scale AI applications without the overhead of traditional infrastructure management. It distinguishes itself from similar tools through its durable execution model and its ability to mix CPU and GPU workloads within a single, unified workflow. With compliance features like SOC 2 Type 2 and HIPAA, along with the option for in-VPC or on-premise deployment for enterprise customers, it offers a secure path for scaling agentic solutions from prototype to full-scale production.
FAQs
What is a Tensorlake Credit?
A credit is the internal currency used to pay for API usage and platform runtime. One credit is valued at $0.01 and is consumed whenever you process documents or run applications on the serverless platform.
Does Tensorlake offer a free trial?
Yes, new users can start on the On-Demand tier, which is a pay-as-you-go plan. This tier includes 100 free credits to help you begin testing the Document AI and Agents Runtime features immediately.
Is the platform compliant with security standards like HIPAA?
Yes, Tensorlake is SOC 2 Type 2 compliant across all tiers. HIPAA compliance and Business Associate Agreements (BAAs) are available for users on the Pro tier or higher.
Can the Document AI handle non-English languages?
Yes, the OCR engine is natively multilingual. It is designed to handle rotated documents, checkboxes, complex equations, and various document formats in multiple languages.
What is durable execution?
Durable execution ensures that the state of your agent is preserved across every tool call, database query, and LLM request. If a process is interrupted, the agent can pick up exactly where it left off without losing progress.
