For your team and clients
The AI governance & workspace.
Your engineers, your contractors and their AI agents work the same projects, and both kinds of worker are treated the same way. Every person gets a role. Every AI agent has an owner and reaches only what that owner allowed.
Built by TEKIMAX, and used on the client software we deliver.
AI rules that compile
Your project's playbook is checked by the platform before anyone works to it, and a rule nothing could ever satisfy is rejected up front. It exports as OSCAL, so your own tools can read it.
A person directs it, and bounds it
An engineer says what needs doing and the AI agent works beside them, reaching only what that engineer is allowed to reach. Every action names both of them, written as it happens.
Connects to the tools the work already lives in
Promoting a model is one decision, made once in Studio. Every call after it, from a terminal or from an agent, is counted against it.
An agent runs on somebody’s authority and never reaches further than they do. Both names go on the record beside the work.
Some things cannot be recalled. Those wait for a person, and their decision is written beside the work with the reason they gave. Everything reversible has already run.
How it works
Your policy stops being a document.
Today your controls sit in a file nothing can check, and proving you followed them means collecting screenshots months later.
Bad rules never ship
A rule nothing could satisfy is refused before your team works to it.
No status reports
Progress is read from the work itself, not written up afterwards.
The audit pack builds itself
Assembled on request from the records, checking as it goes that the log has not been altered.
Theirs to open, not ours
It exports as OSCAL, the US standards format, so your auditor uses the tools they already have.
The controls
The AI agent takes the volume, inside your guardrails.
AI at work should let people get more done, not replace them. That holds only while every action an AI agent takes is one somebody answers for, and every piece of data it touches is handled on terms you set.
- CollaborationTwo names
on every action: the AI agent that ran it and the human it works for. Both sit on the same record, so credit and responsibility are never reconstructed after the fact.
GovernanceNo exceptionsDeploying, merging, and publishing stop before they run and wait for a named human on your side. Reversible work never waits. What was decided, and why, is kept beside the action.
AugmentationMore doneby the same people. An AI agent can hold more work in flight than a person can, and every piece of it still answers to one.
ALOS brings the work together: humans, agents and workflows in one workspace.
humans
agents
Some things cannot be recalled. Those wait for a person, and their decision is written beside the work with the reason they gave. Everything reversible has already run.
workflows
Integrations
Works with the tools your team already uses
What you can hand someone
Three artifacts, and the rest is detail
The record
One sealed history of the work, with the AI agent and the human named on every action. Hand it to a client or an auditor without preparing anything first. It exports in a published standard, at no charge.
Anything not on the list has to be asked for. It is checked when it is used, not promised in a policy.
The parts list
Every package the software is built from, at the version that shipped, with its license beside it. The thing a client's security team asks for, produced by the build rather than assembled for the meeting.
Some things cannot be recalled. Those wait for a person, and their decision is written beside the work with the reason they gave. Everything reversible has already run.
The approval
The moment a named person said yes, kept beside the thing they approved and the reason they gave. Not a timestamp in a separate system that somebody has to correlate later.
What you can point at
Every AI agent has an owner
Every AI agent gets a login of its own and belongs to somebody. It acts for them, never as them, and it can never do more than they can.
- Never a shared key, never a borrowed login, and it never sees a password
- It can only do what its owner may do, and what they approved it to do
- Take somebody off a project and their AI agent loses it too
Anything irreversible waits
Each step's kind is decided in advance, from a written list. Reversible work runs. Work that cannot be undone stops and goes to a named human.
- Deploying, merging, publishing, sending to a customer, and changing how data is stored all wait
- The approval sits beside the work it approved
- A refusal is recorded as carefully as a yes
Everything reversible in this run already finished. This is the only step that waited.
One record, written as the work happens
The record is the product, not a report generated afterward. It is written as the work happens and sealed as it lands.
- Who changed what, when, and under whose authority
- A later edit to the record would show
- Your tasks, reports and connected tools all read the same record
Every line is assigned to whoever acted, and names the human whose authority they used.
Where to start
One platform, two ways in
The mechanism is the same on both sides. What changes is the work it is pointed at, and who signs for it.
StudioSoftware companies, and the forward-deployed engineers and contractors who deliver for them.Agent runsAgent securityApproved modelsScans and approved packagesCommand lineOpen
Customer portalThe client paying for the work, and the people they answer to.Client portalApprovalsAudit trail and evidenceOpen
From the newsroom
What we published lately
Security · standardsThe OWASP LLM Top 10 for 2026.For the first time the list is checked against real incidents, not only expert opinion. The order moved, one risk was renamed, and the guidance underneath is the thing we build for: assume the model gets fooled, and make sure nothing important breaks when it does.Read it
WorkforceBuilding the next generation of AI talent.TEKIMAX invests in workforce development through a Department of Labor Registered Apprenticeship: paid career pathways in AI and cybersecurity, a nationally recognised credential, and no four-year degree required.Read it
Governance · standardsThe NIST AI RMF, at any size.The common language of AI risk in the United States, and the reason your customers are suddenly asking about it. Why a ten-person company needs it as much as a global enterprise, and what it will not do for you.Read it
Talk to us
Tell us what you are building
Say what you are building and who asks you about it. A person reads it and writes back. No demo you have to sit through before anybody answers a question.
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The AI governance & workspace.
Tell us what you are building and who asks you about it. We will show you the record it would leave behind.