Where HexaHQ fits.
HexaHQ gives your AI the context your company runs on, then lets it act in your real systems under your rules. Here's how that compares to the other tools you might be weighing. We link to the real threads and issues behind each one.
Skills vs MCP vs workflows
Skills change how the AI reasons. MCP gives it access. HexaHQ workflows govern what it is allowed to do, and prove it.
HexaHQ vs Claude Teams
Team billing is not team execution. Per-person connector control, a setup your non-technical teammates can run, and governance finer than an on/off toggle.
HexaHQ vs ChatGPT agents
ChatGPT agents run a task for one person, with limits. HexaHQ gets real work done for your whole team, in your real apps.
HexaHQ vs Manus
Manus can repeat a task for one person. HexaHQ runs it for the whole team, under one policy, with an audit trail.
HexaHQ vs Zapier & n8n
They automate well. The question is whose connectors your AI acts through, and who holds the credentials.
Where people keep context for AI today
Most teams have already tried something: a vault, a shared drive, a repo, an enterprise index, or the memory built into their AI. Each of these pages starts with the question people actually search, gives the incumbent real credit, and then explains the point where it stops being enough.
Why can't I just let my AI read our Google Drive?
You can, and you should keep Drive. The hard part is deciding which of four versions of a rule is the one your AI should act on.
Is Glean the context layer for enterprise AI?
A fair read of what Glean does today, and the narrower thing HexaHQ is for: context a company authors and corrects on purpose.
Can I use Obsidian as long-term memory for Claude or ChatGPT?
A vault is good personal AI memory. It shares as a whole, and a company does not. What changes when a second person needs part of it.
Should I keep my AI memory in GitHub?
Git versions text well. Two files stating the same rule in different words merge clean and leave you with two rules.
Can ChatGPT and Claude share the same memory?
Not natively. Your company's AI memory should belong to your company, not to one model. What that means in practice.
AI employees, or AI extensions of your existing team?
Hiring a synthetic generalist buys the resume and skips the accumulated context that made the colleague useful.
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