The Engine for Agentic Work
The complete platform for deploying production agents in the enterprise. Durable execution, document ingestion, and multi-cloud compute — all built-in so you focus on your application, not infrastructure.
Deploy Durable Agents as APIs written in any framework
Process pay stubs, tax forms and bank statements. Verify income automatically.
Ingest claim documents, pull key fields, route to the right workflow. Handle thousands.
Read through agreements, flag key clauses, extract terms.
Document Ingestion enables building Agentic automation faster
Extract key insights, complex tables and charts from investor decks, huge spreadsheets, and SEC filings.
Handle low-quality faxes, handwritten notes, and complex medical forms with ease.
Parse complex intake files into labeled claims data—accelerating adjudication, triage, and system-ready handoff.
Everything you need for Agents in Enterprises
Understanding Documents is the biggest bottleneck for AI Applications. Document AI reads documents effortlessly
An application runtime to run serverless agents in any framework with built-in durable execution to help agents run longer and recover from crashes
Code Sandboxes enables your agents to run untrusted LLM generated code and solve a wide range of problems
Build large scale data ingestion and ETL workflows on CPUs and GPU machines with map-reduce primitives and built-in queues
Average request dispatch time
Number of concurrent requests
Function Input/Output payload size
Serverless Compute for your High Throughput Agents
Tensorlake’s compute platform lets you deploy agents on a serverless runtime to serve them to thousands of users instantly without touching infrastructure.
The platform combines many foundational infrastructure components that typically a platform team have to build, operate and maintain for you to start deploying agents reliably in production environments
State and function calls are automatically checkpointed for hassle free retarts
Pause functions to start after weeks or months
for end-to-end task completion
documents processed per customer a day
Document Ingestion - OCR Infused with VLMs
We use VLMs with OCRs to read Documents the way humans do.
Layout and OCR Models - Break down documents into text, tables, figures while maintaining reading order
VLMs - Read images, complex tables, correct OCR mistakes and classify documents based on visual context
Get server-less runtime for agents and data ingestion
Tensorlake is the Agentic Compute Runtime the durable serverless platform that runs Agents at scale.
"For BindHQ customers, the integration with Tensorlake represents a shift from manual data handling to intelligent automation, helping insurance businesses operate with greater precision, and responsiveness across a variety of transactions"
“Tensorlake let us ship faster and stay reliable from day one. Complex stateful AI workloads that used to require serious infra engineering are now just long-running functions. As we scale, that means we can stay lean—building product, not managing infrastructure.”
The All-In-One Runtime for AI Data Workflows
Built-in 1TB persistence layer. Ingest massive datasets without managing Kafka or Redis sidecars
from tensorlake import function, File
@function()
def download_dataset(path: str) -> List[File]: images = load_images(path)
return [pre_process_image(image) for image in images]
@function(gpu="A10")
def detect_objects(image: PIL.Image) -> Detection:
detection = yolo(image)
return detection
@function()
def write_to_db(detection: Detection): psql.write(dection)
Achieve data-warehouse concurrency directly in Python. Use .map() to fan out execution across thousands of nodes instantly, replacing the need for SQL-based orchestration
Concurrent invocations per workflow. Zero cold-start throttling
Attach H100 GPUs to any step via a single decorator argument. Mix CPU and GPU workloads in the same workflow.
Full traces of every function and tool call — with logs, timing, and structured execution paths.
Tool calls run in isolated sandboxes, making them safe for LLM-generated code.
Each agent harness executes inside an isolated sandbox to keep sessions safe and independent.
Secure by default for PHI, PII, and sensitive documents.
Each project’s data lives in its own isolated bucket with full audit trails and strong RBAC controls.
