Give each project its own AI workspace.Keep agents, people, and memory in sync.
MeMesh lets each workspace act as an independent project: assign AI agent roles, connect authorized LLM models, track roadmap progress, and keep project memory from leaking into unrelated work.
MeMesh is now in Alpha release
Access is currently limited while we learn from early feedback. If you want to try it, request Alpha version access first.
Why teams use it
A clearer path from request to result
Each project gets its own workspace
Story bibles, posting schedules, website notes, source docs, agents, and teammates stay attached to the project they belong to.
Roadmap and agent progress are visible
See what agents are doing, what is blocked, what needs approval, and what changed in the project.
Knowledge can come from the tools you already use
MeMesh is designed to bring approved Obsidian, Google Drive, and local MeMesh sources into the selected workspace knowledge graph as the connector path ships.
Get started in 3 simple steps
You do not need to learn a complex system first. Set up one workspace, try one real task, and see if the flow works for you.
Create your account
Start with your own space so you can try things safely before inviting others.
Connect the AI tools you already use
Bring your provider or agent into MeMesh so work can run from one place.
Start work and review results
Give AI a task, follow the progress, and approve important results before moving on.
Why it feels clearer
More than chat: it keeps AI work organized
MeMesh separates your personal space, team space, progress, and review so the work is easier to understand.
No shared login, no confusion about who changed what
Each person uses their own account. Team work starts when people join the same shared workspace.
Everyone has their own space
You can try, learn, and prepare before you affect the team.
Team work lives in one shared workspace
The whole team can see the same tasks, approvals, and next steps.
You can always look back at what happened
Results and decisions stay attached to the work, so follow-up is easier.
Why teams can trust the workflow
Review important output before it is used
Put a human check in front of sensitive or important results.
See where each task stands
Know what is running, what is waiting, and what needs help.
Keep a record of decisions
You can look back at what happened and why a result was accepted.
Break bigger work into trackable steps
Larger tasks are easier to follow when they are split into smaller parts.
Invite teammates with the right access
Share the work without sharing one login or giving everyone the same permissions.
Connect your own AI tools
Bring the providers, agents, or runtimes your team already trusts.
Already have your own agents or AI tools?
Bring them into one workspace, test the real flow, and decide later how far you want to roll it out.
Currently in Alpha release
Start by checking whether this solves the right problem
If you want AI work to feel less chaotic, easier to review, and easier to run with a team, this section helps you decide whether MeMesh matches that need.
Start by seeing whether the product matches the way you actually work. If it does, request Alpha version access.
- Built for people trying to reduce AI workflow confusion
- Important output can be reviewed before it is used
- Teams can follow the same work in one place
- Request Alpha version access if the fit looks real
If this sounds like your problem, request access.
If you want clearer AI work, safer result review, and less team coordination drift, tell us about your workflow and we will follow up.