The product

Teach AI how your organization works as you work.

HexaHQ captures the facts, rules, preferences, processes, and corrections that matter, then gives each AI task the relevant context before it decides or acts.

Capture

What came up while the work was being done.

Learn

A correction, kept with who made it and where it applies.

Reconcile

One current version of each thing your company believes.

Resolve

The parts that apply to the task in front of you.

Act

The decision, and the change in the real system.

Under your organization's rules

Captured during real work

Your AI writes down what mattered.

Ask for an outcome you already need. As it works, your AI saves the facts, preferences, and repeatable steps that should survive the chat. Nobody has to stop and build a documentation system on the side.

One real task

Prepare our product launch.

What is true and what the rules are

Facts, decisions, preferences, and the reasons behind them. HexaHQ stores these as knowledge documents.

How the job gets done here

The steps that worked, so a repeatable job does not get rebuilt from scratch. HexaHQ calls these workflows.

Learning from correction

Correct it once. The lesson is there next time.

Correction is not an error state. It is the main way an organization teaches AI how it actually works, and HexaHQ treats it that way.

1

The AI gets a decision wrong

It puts a discount in the follow-up, because nothing told it legal has to sign off first.

2

You correct it while you are working

You say what the rule actually is, in your own words. No form, no separate knowledge base to open.

3

HexaHQ keeps the correction

It records the rule, who it came from, and where it applies, and shows you what it wrote so you can change or discard it.

4

Later work starts from it

The next task the rule applies to gets it without anyone repeating themselves.

A correction does not become a rule for everyone on its own. HexaHQ keeps its scope, its source, and where it applies, so one person's preference is not mistaken for company policy.

One evolving source of truth

One concept, not five copies drifting apart.

The problem is rarely that a fact was never written down. It is that it was written down four times, in four places, and only one of them was updated. HexaHQ keeps the current, canonical version and the information needed to tell whether it applies to you.

How company context is kept →
Versions
Change an approved fact once. Work that uses it after that starts from the new version.
Duplicate concepts
When two documents describe the same thing in different words, HexaHQ can propose merging them and let a person decide.
Authority
Who set a rule is kept with the rule, so a claim can be weighed instead of guessed at.
Personal and company copies
Your own way of doing something can sit beside the company rule without overwriting it.
Audience
Who a piece of context reaches is a property of the context, not a second copy of the file.
Resolved for the task

The right context, chosen for the task at hand.

This is the step between knowing something and doing something well. Before the AI decides or acts, HexaHQ works out which parts of your organization's context apply to this task, for this person, and hands over those. The goal is the smallest set of context that changes the decision.

The task

Send the follow-up from this morning's Acme call.

Applied

Discount approval rule Current pricing What Acme was told last quarter How Priya writes a follow-up

Left out

Bug severity rules Release checklist Everyone else's writing style

Irrelevant context is not free. It makes decisions worse, not just slower, so choosing well matters more than fitting more in.

Acting on it

Use the context to finish the work.

Once the AI has the rules and facts that apply, HexaHQ can help it carry the decision into the systems where the work actually happens. A capability is a specific action in a connected system, and it runs with the context that guided the decision.

Existing MCP server

Connect its tools through HexaHQ under your organization's rules.

REST or GraphQL API

Turn the API into the specific actions the AI needs.

Internal or niche system

Create a capability without waiting for a catalog listing.

How HexaHQ connects any API →

Shared where it helps

One person's expertise can improve everyone's work.

Creating context and distributing it are separate steps on purpose. Review what your AI saved, then decide how far it goes. When the person who knows the rule teaches it once, the people it applies to get it without being taught again.

What this looks like for a team →
Personal
Writing style, preferences, and private working notes stay available only to you.
Selected people
Give a team, project group, or executive group only what applies to their work.
Organization
Publish approved facts and processes for everyone who should be working from them.
External
Use a Collection to share a controlled set with a client, partner, agency, or advisor.
Independent of the model

Keep company context outside the model.

The knowledge and working rules your organization depends on should survive a change in AI client. HexaHQ keeps that durable state separate from any one model vendor.

ChatGPT

Works out the launch strategy.

HexaHQ

Holds how your organization wants this done.

Approved positioning Launch process
Claude Code

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.

Why your context should not belong to one AI →

Organization control

Decide what AI may do.

Your organization can allow routine actions, require approval for sensitive ones, or block an action entirely.

Security and governance →
  • Individual identity

    People use their own logins and their own access to each connected app.

  • Action-level policy

    Allow, require approval, or block an individual capability.

  • Audit history

    See what ran, who authorized it, and when it happened.

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.