Tensorlake
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About
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.
Pros & Cons
Durable execution prevents progress loss during system interruptions or API failures.
Built-in 1TB persistence layer removes the need for managing external Redis or Kafka sidecars.
Layout-aware parsing accurately handles complex documents like invoices, charts, and tables.
Serverless GPU attachment allows mixing CPU and GPU workloads via simple Python decorators.
Offers SOC 2 Type 2 and HIPAA compliance for sensitive enterprise data processing.
High-performance H100 GPU access is restricted to the Enterprise pricing tier.
The On-Demand tier is limited to only two concurrent functions.
Pro tier requires a significant $500 monthly base fee plus usage credits.
Log and history retention is limited to seven days on the base On-Demand plan.
Use Cases
Enterprise developers can build complex agentic workflows that maintain state and resume automatically after failures.
Data engineers can automate the ingestion of millions of unstructured documents using layout-aware parsing without managing infrastructure.
Software architects can safely run LLM-generated code by utilizing isolated sandboxes for every session.
Compliance officers can manage sensitive healthcare data by utilizing the HIPAA-compliant Pro tier with BAAs.
Machine learning teams can scale GPU-intensive tasks across thousands of nodes using simple Python function decorators.
Platform
Task
Features
• application observability
• no-sql parallelism
• 1tb built-in persistence
• serverless gpu compute
• isolated code sandboxes
• structured extraction
• layout aware parsing
• durable execution
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.
Pricing Plans
Pro
USD500.00 / per month• 50,000 Credits Included
• 1 TB Data Ingestion Queue
• 100 Concurrent Functions
• HIPAA and SOC 2 Type 2
• 30 Days History and Logs
• Role-Based Access Control
• Document AI ($0.01/page)
• Priority Slack and Email Support
• Business SLA (24 Hours)
• Bring Your Own Storage
Enterprise
Unknown Price• Unlimited Concurrent Functions
• H100 GPU Access
• In-VPC or On-Premise Deployment
• SSO and SAML Authentication
• Fixed SLA for Latency
• White Glove Onboarding
• Dedicated Resident Solutions Architect
• Custom Rate Limits
• Custom MSA
• P1 SLA (1 Hour)
On-Demand
Free Plan• 100 Free Credits
• 100 MB Data Ingestion Queue
• 2 Concurrent Functions
• Code Sandboxes
• Durable Execution
• SOC 2 Type 2 Compliant
• 7 Days History and Logs
• Document AI ($0.03/page)
• Self-Serve Documentation
Job Opportunities
Senior Product Engineer
Deploy production-ready AI agents with durable execution, automated document ingestion, and serverless compute to build scalable enterprise applications faster.
Experience Requirements:
5 or more years of experience in product engineering
Other Requirements:
Strong understanding of frontend architecture and REST APIs
Ability to lead, design, and implement product experiences end-to-end
Knowledge of Rust or curiosity to learn it
Proficiency in Next.js, TypeScript, and PostgreSQL
Knowledge of Python
Great written and verbal communication skills
Responsibilities:
Craft intuitive interfaces and APIs for document and workflow management
Build features end-to-end, from playground to subscription services
Work with engineering team to take ideas to polished products
Define tasks, implement them, and monitor success
Optimize browser JavaScript for performance
Show more details
Ratings & Reviews
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