The Control Plane for
AI-Native Work
The always-on control plane for knowledge work—proactively orchestrating your emails, chats, tickets, and code.
Join ... others on the waitlist
Knowledge work is
fragmented and reactive
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1
Fragmented Signals. Important context is scattered across email, Slack, Jira, and GitHub, forcing you to constantly context switch.
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2
High Cognitive Load. You spend hours manually monitoring inputs and reconstructing context instead of doing deep work.
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3
Missed Actions. In the chaos of notifications, critical follow-ups slip through the cracks.
Fragmented Context
Mnexa: Proactive, context-aware AI
embedded in your work
I noticed a request for the Q3 roadmap in this thread. I've prepared a draft reply with the link to the Linear project.
Proactive Orchestration
Runs in the background without needing prompts. It observes, anticipates, and prepares workflows before you even ask.
Context as a First-Class Primitive
Unlike chatbots, Mnexa understands the full state of your work—screen, apps, and data—connecting the dots across tools.
Cursor-Level, In-Flow UX
Embedded directly where you type. No need to switch contexts or open a side panel; AI help appears at the moment of intent.
Built for High-Context Teams
Designed specifically for product and engineering workflows that span complex stacks like Jira, Linear, GitHub, and Slack.
Core Use Cases
Proactive Orchestration
Runs in the background without needing prompts. It observes, anticipates, and prepares workflows before you even ask.
New Feature Request
Customer requesting dark mode support...
Prioritized as Important. Suggested workflow:
Responsive Event Handling
Never miss a critical signal. Mnexa catches urgent emails, messages, and tickets, prioritizes them, and drafts executable workflows for you to review.
What's the status on the customer report?
Use status from LIN-2401:
"Fixed in v2.4, deploying today."
Cursor-Level, In-Flow UX
Embedded directly where you type. No need to switch contexts or open a side panel; AI help appears at the moment of intent.
Recent benchmarks indicate that transformer-based models outperform LSTM architectures by 15% in complex reasoning tasks, suggesting a shift in our core strategy is warranted.
Context at Your Fingertips
Mnexa AI connects your entire workflow, bringing relevant context from across your tools directly to executable workflows.
Request Early Access
Be among the first to experience the future of knowledge work.
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Thanks for your interest in Mnexa AI. We'll reach out to you as soon as a spot opens up.