Get back to your project without starting over.
You open a project you worked on last week. The research is in your browser history, the plan is in a chat, and you know you changed direction somewhere along the way.
Before you can move forward, you have to find your place again.
We're building Chaser Agent for that moment.
ChaseOS keeps the notes, sources and decisions connected in a knowledge graph. Chaser Agent is being built to help you work with that context and prepare your next step.
You should be able to see where a suggestion came from, question it, and change direction without losing the work behind it.
Watch the film for a look at Chaser Agent and the ChaseOS graph, then explore how it fits the way you work.
chaseos.ai/chaser-agent
Chaser Agent makes approval, correction, blocked routes, provenance and completion visible.
Standalone-first. ChaseOS-enhanced for shared governance, routing and cross-project memory.
P0.1 development preview—not released.
github.com/chasedndt/Chaser-…
See the new ChaseOS Security & Responsible Disclosure page in motion.
Private reporting. Clear testing boundaries. Evidence-led remediation. Honest pre-bounty status. A consent-based Hall of Fame.
Thank you to Pavan Baile for reporting responsibly.
chaseos.ai/security
ChaseOS now has a Security & Responsible Disclosure page: private reporting, clear research boundaries, an evidence-led response path, honest pre-bounty status and a consent-based Hall of Fame.
Thank you to Pavan Baile for a responsible contribution.
chaseos.ai/security
Your agents need shared context.
When chats, tools and runtimes start from different project truth, capable systems make brittle decisions.
ChaseOS connects projects, sources, workflows and agent activity in one local-first operating layer.
Explore: chaseos.ai/?utm_source=x&utm…
ChaseOS Studio V1.0.6 updates without sending you back to the website.
Review the release. Choose Update now. Studio downloads, verifies, installs and reopens—while your workspace stays outside the installer.
Explicit. Signed. Operator-approved.
chaseos.ai/download
21 steps. One clear first run.
ChaseOS Studio V1.0.6 guides new users from their workspace to Hermes or OpenClaw, Windows or Ubuntu defaults, the native Terminal, ChaseOS Cloud and connectors.
First use by default. Replayable from Help.
chaseos.ai/download
ChaseOS Studio V1.0.6 is live for Windows.
Cloud setup, made clearer:
• better key diagnostics
• recoverable Hermes/OpenClaw setup
• protected provider backups
• signed-build evidence bound to the installer
chaseos.ai/download
🤖 Made with AI
ChaseOS Studio V1.0.6 is live for Windows.
Clearer Cloud-key diagnostics. Recoverable Hermes/OpenClaw setup. Protected provider backups. Stronger signed-build acceptance.
Download: chaseos.ai/download
Changelog: chaseos.ai/changelog
ChaseOS Studio V1.0.5 is available for Windows 10/11 x64.
The signed release connects first run to real operation: Hermes/OpenClaw setup, Windows/Ubuntu launch defaults, reversible ChaseOS Cloud configuration, Chat, the linked Graph, Discord guidance, and in-app updates.
chaseos.ai/download?utm_sour…
ChaseOS Studio V1.0.5 is live for Windows.
Install Hermes or OpenClaw, choose Windows or Ubuntu, configure reversible ChaseOS Cloud, use Chat + the linked Graph, and add Discord for mobile control. Signed updates now install inside Studio.
chaseos.ai/download
An approval gate is not a polite confirmation dialog.
It should bind the exact action, destination, data, cost, and expiry—then fail closed if any of them change.
That is how governed AI stays useful without becoming unbounded.
chaseos.ai/blog/human-approv…
An AI agent that passes once is not necessarily reliable.
A useful evaluation pins the task packet, source snapshot, allowed tools, expected effects and acceptance checks. It also records retries, cost, human intervention and recovery—not just the final answer.
Then rerun the same case after every model, prompt, tool or policy change.
That turns “it worked” into comparable evidence.
Our practical guide to reproducible agent evaluations:
chaseos.ai/blog/reproducible…
Could ChaseOS use DeepSeek V4 for repository-scale engineering without handing a model the keys?
This reference design uses R2 workspaces, Workers policy, typed checkpoints and exact receipts.
chaseos.ai/blog/cloudflare-e…
AI-agent failures rarely start with the model alone. They emerge between memory, tools, permissions, retries and side effects.
Our architecture-audit guide maps 10 failure families and the evidence to demand:
chaseos.ai/blog/ai-agent-arc…
#AIAgents
Agent memory is a security boundary.
Poisoned content can wait in durable memory for a later session. ChaseOS holds captures for review before they join the local graph. Remembered text never grants tool authority.
Explore: chaseos.ai/
#AISecurity #AIAgents
Claude's watermark is not a security boundary. Use Claude for research, hand over a typed task packet, then switch models for implementation and independent review. Build it in ChaseOS:
chaseos.ai/blog/claude-water…
ChaseOS Studio v1 is live.
Start free with Community, or choose Pro, Studio Plus or Studio Max for more managed Cloud credits and headroom.
Your workspace stays local-first. Your agents stay under your control.
Plans: chaseos.ai/pricing













