One shared context for people and AI to get work done together.
HexaHQ automatically captures how your organization works, learns from corrections, and gives AI the context it needs to make decisions and take action the way your team would.
Free to start. Hand your AI a real piece of your job in about a minute.
Send the follow-up from this morning's Acme call.
We never put a discount in writing before legal signs off.
Draft the renewal note for Northwind.
The rule is applied before the draft is written
Most of how your company works was never written down.
Documents capture facts and policies. The harder part lives in people: which exceptions matter, how systems are really used, and what experienced teammates know to do without thinking about it. HexaHQ keeps those lessons as work happens, then sorts out which version is current and where it applies.
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Do real work
Ask your AI for something you already needed today.
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Correct it in passing
Say what it got wrong, the way you would tell a coworker.
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The lesson is kept
HexaHQ saves the correction and shows you what it wrote down.
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It shows up next time
Later work that the rule applies to starts with it already in hand.
A correction does not quietly become a company-wide rule. HexaHQ reconciles it with what your company already says, so you can see whether it updates an existing rule, holds for one team, or needs someone to settle it. That is what makes the same rule mean the same thing wherever it comes up.
The right context for the work in front of you.
Two people on the same team need two different things. HexaHQ gives each task the company context that applies plus the context personal to the person doing it, and leaves the rest out. More context is not better context.
Send the follow-up from this morning's Acme call.
- From the company
- Discount approval Current pricing Approved security answers
- Personal to this person
- How Priya writes a follow-up
- Left out
- Bug severity rules Release checklist
File the bugs we found in the launch review.
- From the company
- Bug severity rules Release checklist Who owns which service
- Personal to this person
- How Sam writes a ticket
- Left out
- Discount approval Current pricing
Give AI parts of the job, not just questions to answer.
With the right context in hand, your AI can carry a piece of your work through to a decision or a real change in a real system. You stay in it where the call actually matters.
Write up the call in the CRM
It applies your rules for what counts as a qualified opportunity, updates the record in Salesforce, and asks you first when the amount crosses your approval line.
Triage the incoming bugs
It sorts new reports by your severity rules, files them in Linear with the right owner and priority, and leaves the ambiguous ones for a person to call.
Answer the security questionnaire
It fills in the answers your company has already approved and flags the questions nobody has answered yet, instead of inventing one.
Each of these is a specialized piece of one person's job, done with the context that person would have given a new hire.
What one expert teaches AI can help the whole team.
When the person who actually knows the rule corrects the AI, that correction does not have to stay with them. Keep it to yourself, give it to one team, or publish it for the organization. Nobody has to teach the same thing twice, and what one person teaches AI does not leave when they do.
- Personal
- Your writing style, your preferences, and the working notes you would not send anyone.
- Selected people
- Give one team or project group the rules that apply to their work and nothing else.
- Organization
- Publish the approved facts and processes everyone should be working from.
- External
- Package a controlled set for a client, partner, agency, or advisor without opening up the rest.
Launch positioning
One source, controlled access
Your company's AI memory should belong to your company.
The rules, corrections, and saved ways of working live in HexaHQ, not inside one model's memory. Supported AI clients read the same organizational context, so changing which AI you use does not mean teaching it everything again.
Works out the launch strategy.
Holds how your organization wants this done.
Builds from the same approved material.
HexaHQ carries only what was saved to it. It does not copy every conversation or hidden model state between AI tools.
The same context can guide the action.
Knowing the right thing is what makes acting reliably possible. When the task needs another app, HexaHQ can use an existing MCP server or create a narrow capability for an ordinary API. If it has an API, HexaHQ can work with it.
Already has an MCP server
Connect it through HexaHQ and make it available under your organization's rules.
Only has an API
HexaHQ turns the API into tools the AI can use.
Internal or niche system
The AI can create the capability it needs without waiting for a catalog listing.
Your organization decides what AI can do.
Once AI acts in real systems, the stakes change. Each person works through their own account. Reads can run automatically. Sensitive actions can require approval or be blocked, and HexaHQ records what happened.
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Individual identity
People use their own logins and their own access to each connected app.
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Action-level policy
Allow, require approval, or block an individual capability.
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Audit history
See what ran, who authorized it, and when it happened.
Add HexaHQ to the AI you already use.
Start free for guided setup. If you prefer to configure the connection yourself, use the HexaHQ MCP endpoint shown here.
{
"mcpServers": {
"hexa": {
"url": "https://mcp.hexahq.ai/mcp/"
}
}
}
Uses OAuth. You'll approve access in the browser the first time your client connects.
Give your AI a real piece of your job.
Start with work you already need to do. Correct what it gets wrong, and it will not need telling twice.