AI governanceHuman augmentation
Govern the build. Augment the human.
Every person gets a role. Every AI agent has an owner and reaches only what that owner allowed. Every action names both, on the record, as it happens. What your people learn from it stays theirs.
Built by TEKIMAX, and used on the client software we deliver.
Do more with the team you have
AI agents take the volume. People take the calls that need judgment, and get to them with time left over.
Answer it six months later
Which part the AI agent did, which part the person did, and who said yes to what could not be undone. Written as it happened.
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 that somebody signs for it first. 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 goes
Four steps, and the first one never finishes
Deciding what may run is not a setup task you finish. Each turn shows you what actually ran, where, and how much of it waited, so the next decision is made by somebody who knows more about their own work than they did last month. The platform does not learn this for you. You do, and it is yours to keep.
- 01
You decide what may run
Which models and which skills your organization allows, set in Studio and changed there whenever the picture changes. A project can narrow it, nothing can widen it.
You, and again - 02
Your people work as they already do
An engineer signs in from their terminal. Their AI agent connects over MCP and inherits their limits, never reaching further than the person it acts for.
Your team, daily - 03
Anything permanent stops
Deploying, publishing, sending to a client: each one waits for a named person, who says yes or no in writing, with the reason kept beside the work.
A named human - 04
You see it, and you learn from it
The record and the parts list are already written. Read them yourself and you learn what an AI agent is good at on your own work, not in the abstract.
Then round again, knowing more
The controls
Nothing runs that you did not allow.
AI at work should let people get more done, not replace them. That holds only while every action an agent takes is one somebody answers for, and every piece of data it touches is handled on terms you set.
CollaborationTwo nameson every action: the 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, because the agent takes the volume and the human keeps the judgment. Nobody is replaced to pay for it.
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 agent and the human named on every action. Hand it to a client, an insurer, or your own board without preparing anything first. Nobody has to reconstruct the month.
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
Your AI agent signs in as itself, on your behalf
Point a coding agent at the platform and it works the rest out: the instructions for signing in are a public document at the API's own address. It registers itself, then asks you to approve the sign-in in a browser you already trust. What it comes back with is its own identity carrying your authority, not a copy of your password and not a key pasted into a script.
- The instructions for signing in are open, so an agent needs no credentials to learn how to get credentials
- You approve it in your own browser, and it never handles your password
- What it may do is the overlap of two lists: what you may do, and what you approved it to do. Never the wider of the two
- Narrow either side and the agent narrows with it, as a consequence rather than a second job
Every agent has an owner
An agent belongs to the person who created it. It acts for them, never as them, and it appears as theirs in every list, every filter, and every line of the record.
- Never a shared key and never a borrowed login
- Capped by its owner's permissions, and narrowed further per tool and per project
- Every change carries the agent's name and its owner's, in the same entry
- Switch one off in seconds without touching the others
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 this, when, and under whose authority
- Which model ran, and what it was allowed to do
- A later edit to the record would show
- Tasks, client reports, and the tools you connect all draw from the same record
Every line is assigned to whoever acted, and names the human whose authority they used.
The features
Everything it does, and what each one is for
- AI management systemAgent runsGive an agent a job, then read back every step of it.Read the page
- GovernanceApprovalsAnything that cannot be undone is assigned to a human.Read the page
- GovernanceAudit trail and evidenceWho did what, on a sealed record, exported when someone asks.Read the page
- Forward-deployed engineeringClient portalDocuments, signing, progress, invoices and tickets, in one place.Read the page
- GovernanceScans and approved packagesApproved packages at the exact version, checked when used.Read the page
- AI management systemMCP serverConnect any AI agent, and the rules come with it.Read the page
Earn while you learn
Train the people who run your agents
AI Solutions Specialist is a registered apprenticeship, and the hours and sign-offs land on the same record as the work.
- They learn on real client work, beside a mentor, from the first week
- They move on by showing what they can do, not by serving out the months
- TEKIMAX carries the registration; you provide the work and the mentor
AI Solutions Specialist
U.S. Department of Labor registered · Competency-based
About us
Built for teams who keep AI inside the lines
TEKIMAX is a Fort Worth software company. We build AI systems that stay inside the limits the people running them set, because most tools built around AI quietly take the human out of the loop.
The obvious objection is that a human in the loop slows everything down. It would, if you put one on every step, so we do not. Reversible work runs without waiting. Only what cannot be undone stops for a named human.
Christian Kaman is the founder and CEO of TEKIMAX Inc., a Fort Worth company building ALOS, a platform that makes forward deployment virtual: engineers and their agents work inside a customer's environment, on connections the customer owns and can switch off.
Reversibility sits at the core. Every action is either safely undoable, or held for a named human to approve.
Christian Kaman
Founder and CEO, TEKIMAX Inc.
Master's in Data Science
Where to start
One platform, three ways in
The mechanism is the same in all three. What changes is the work it is pointed at, and who signs for it.
Forward-deployed engineeringAgencies and contract engineers whose client work has to carry names when it is handed over.Open
GovernanceTeams that want controls on their AI, so it does what it is supposed to and nothing else.Open
An AI management systemFor a company running agents that is not a software company, including the small one with no compliance function.Open
Govern the build. Augment the human.
Tell us what you are building and who asks you about it. We will show you the record it would leave behind.
What you can answer afterward
- Which agent did this, and who owns it
- What that agent was allowed to touch, and what it touched
- Who approved the release, and what they were told at the time
- Who owns the work, and what you can take elsewhere