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EXCEPTIONS SURFACEDBUILT FOR YOUR BUSINESS
Managed AI workflow deployments
- SECURE
- SANDBOXED
- MANAGED
Worktree maps a recurring business process, builds the agent workflow into your existing tools, then manages evaluations, quality control, and improvements after launch.
Personal Agent
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#sales
#projects
Agent
AgentToday’s priorities, prepared for review
Yesterday
Message Agent
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Message Agent
Connects across1,000+ tools
The cost of manual follow-through
Important busy work is still busy work.
Follow-ups, approvals, updates, and handoffs all matter. But when your best people carry them across tools by hand, they lose time for the work that actually transforms the business.
Worktree turns that follow-through into managed agent routines, so the business keeps moving and your team gets back its best hours.
Research
Data pulled from every tool.
SOURCES PULLEDAnalyze
What matters rises to the top.
PRIORITY FOUNDDraft
Replies and briefs ready to review.
DRAFT READYIllustrative workflow
One request becomes a controlled agent run.
Worktree should not feel like another place to chat with AI. A teammate triggers a known workflow, and the run moves live across systems with scope, approvals, artifacts, and history visible from start to finish.
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#general
#sales
#customer-success
Worktree
#salesPipeline, pricing & deals
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Where to start
Start with the work that already has a playbook.
The best first workflow is recurring work your team already understands, but still handles manually because it needs context, judgment, and access to several systems.
Ready for a managed routine
Good first workflow
- Happens frequently
- Has a known playbook
- Uses clear inputs
- Needs context from several systems
- Has clear success criteria
Needs more definition first
Bad first workflow
- Happens once or rarely
- No one agrees what good looks like
- You cannot define the process
Pick the right workflow
Choose recurring work with clear inputs, business value, and a known way to judge success.
Map the real process
Capture the systems, rules, exceptions, approvals, handoffs, and expected outputs behind the work.
Build it into operations
Create the agent workflow, connect the tools, define boundaries, test real cases, and launch it where the work already happens.
Managed quality
Review real runs against the agreed standard, fix weak spots, and make focused improvements that keep the workflow reliable.
How it works
We turn real business processes into managed agent workflows.
We map how the work happens today, build the agent workflow, insert it into daily operations, and manage quality after launch so each routine can prove itself in production.
Managed quality
Evaluate the workflow, supervise the runs, improve what matters.
After launch, we review real runs against the agreed standard, watch approvals and exceptions, and make focused improvements that keep the workflow reliable.
Quality standard
We agree what good looks like before launch, then use that standard to review real workflow runs.
Approvals supervised
Sensitive steps stay visible, with human approvals reviewed after launch so the routine keeps the right boundaries.
Exceptions caught
Failures, edge cases, missing context, and unclear handoffs are tracked from live runs instead of hidden in chat history.
Focused improvements
We ship targeted fixes from evidence, not broad rebuilds, so quality improves without expanding the workflow scope.