OpenClaw + BitSageNew

Agentic AI Workflows On Private Infrastructure

Build and deploy autonomous AI agents that run on confidential compute. Your agents, your data, your control.

Try OpenClaw
Input
Agent
Tools
LLM
Output
# Define your agent
from openclaw import Agent, Tool
# Runs on BitSage confidential compute
agent = Agent(
model="claude-3-opus",
tools=[web_search, code_exec, file_io],
memory=True,
private=True # TEE execution
)
result = agent.run("Research competitors and create report")

Why OpenClaw + BitSage?

The power of autonomous agents with the security of confidential compute.

Autonomous Agents

Deploy AI agents that think, plan, and execute complex multi-step workflows without human intervention.

Workflow Orchestration

Chain together LLMs, tools, APIs, and custom logic into automated pipelines.

Model Agnostic

Use GPT-4, Claude, Llama, or any model. Switch providers without changing your workflows.

Memory & Context

Agents maintain context across sessions with built-in vector storage and retrieval.

Privacy-First

Run on BitSage confidential compute. Your data and prompts stay private with encrypted execution.

Enterprise Security

SOC2 compliant infrastructure with audit logs and access controls.

Use cases

Build anything autonomous

From research assistants to code generators, OpenClaw agents handle complex tasks end-to-end.

Research Automation
Agents that search, synthesize, and report on any topic.
Code Generation
Generate, test, and deploy code autonomously.
Data Processing
Transform, analyze, and visualize data at scale.
Customer Support
AI agents that resolve tickets end-to-end.
Private by default
Prompts encrypted end-to-end
Agent memory stored privately
Tool outputs never logged
Encrypted execution environment
Zero data retention option

Start building AI agents today

Deploy autonomous workflows on privacy-first infrastructure. Free tier available.

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