Most AI agents are blind. They run without real company context and stop after isolated tasks. Donely Knowledge Layer gives your AI employees a queryable company brain connected to meetings, docs, chats, tickets, and codebases. This enables closed-loop workflows where agents can understand context, take action, observe outcomes, and continue work autonomously. Your AI employees can now understand what happened, what’s happening, and what needs to happen next.
Hey Product Hunt, Harsha here, founder of Donely.
We started Donely because OpenClaw is powerful, but running it in production is still painful.
You need setup, infra, uptime, credentials, channels, memory, and someone to fix things when it breaks. That’s fine for hackers. It’s not fine if you’re a founder, agency, or business trying to actually use AI employees every day.
So we built Donely.
Today, Donely lets you deploy and manage OpenClaw-powered AI employees in the cloud. Each instance is isolated, has its own access, channels, billing, and AI repair layer.
But the bigger vision is what I’m most excited about:
AI employees should not be blind.
They should understand your company.
So we’re building a queryable company brain underneath them. Meetings, tickets, docs, code, customer conversations, all connected into one knowledge layer your AI employees can reason over.
That means your AI employee can know what happened, what is stuck, what was promised, what shipped, and what needs to happen next.
This is the start of AI Founder Mode for us.
A founder or team should be able to run a company with a super-agent layer underneath them, helping them stay in the details without drowning in them.
Would love your feedback, support, and brutal honesty. We’re building fast.
Can you walk through how “isolated by design” works in practice—compute/container boundaries, network egress controls, secret storage/rotation, and approval flows—and how you make audit logs useful enough for real forensics rather than just debugging?
Super cool. I find that local implementations are very limiting, since I am using multiple devices daily. Is the AI repair related to managing version upgrades? I am building klodi, a plugin for openclaw (agentic marketplace), and version upgrades are my biggest headache tbh.
About Donely Knowledge Layer on Product Hunt
“Queryable company knowledge base + Closed-loop AI employees”
Donely Knowledge Layer launched on Product Hunt on May 8th, 2026 and earned 98 upvotes and 3 comments, placing #17 on the daily leaderboard. Most AI agents are blind. They run without real company context and stop after isolated tasks. Donely Knowledge Layer gives your AI employees a queryable company brain connected to meetings, docs, chats, tickets, and codebases. This enables closed-loop workflows where agents can understand context, take action, observe outcomes, and continue work autonomously. Your AI employees can now understand what happened, what’s happening, and what needs to happen next.
Donely Knowledge Layer was featured in YC Application (46 followers) on Product Hunt. Together, these topics include over 553 products, making this a competitive space to launch in.
Who hunted Donely Knowledge Layer?
Donely Knowledge Layer was hunted by Harsha Abegunasekara. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Donely Knowledge Layer stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Harsha Abegunasekara