AI governanceHuman augmentation

Govern the build. Augment the human.

Govern, map, measure and manage, with the evidence produced by the work itself rather than assembled afterwards for an audit.

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Built by TEKIMAX, and used on the client software we deliver.

Membership is not an endorsement.

Do more with the time you have

Humans working with AI finish more work, faster, and to a higher standard. The time it frees goes to judgement and the bigger picture.

Stay answerable for every action

A tamper-evident record of what happened, and a named person who can stop anything irreversible. Every framework asks for those two.

Connects to the apps the work already lives in

A contract open in the editor with the authorship lens on: every sentence underlined by where it came from, and a panel counting how much of it was typed, pasted or written by an AI agent

Document AI

Nothing changed yet

Ask, draft, and place the answer

Plan6 steps

Add a Statement of Work section covering scope, deliverables, timeline, acceptance and fees, after the general provisions and before the signature blocks.

1Insert the Statement of Work heading and an opening paragraphwhere After the counterparts paragraphwhy A statement of work needs its own heading and its context before it details any scope
2Add a Scope of Work subsectionwhere Under the new headingwhy Scope is what says which work is being commissioned
3Add a Deliverables subsection with acceptance criteriawhere Under the new headingwhy Deliverables and acceptance are what say when the work is finished

Write itRefineEdits arrive tracked

Nothing here runs until a person says so, and the decision is written down with their reason, on the same record as the work.

Responsible AI at work

Augment humans. Govern every action and record.

AI at work is for humans to get more done, not to be replaced. That holds only if every action an AI agent takes is one somebody answers for, and every piece of data it touches is handled on terms you set. Both are recorded as the work happens.

CollaborationEvery action
is taken by a named AI agent or a named human, in the same place and on the same record. The work is shared rather than handed over, so credit and responsibility are never a guess.
GovernanceNo exceptions
Deploying, merging and publishing stop before they run and wait for a named person. Reversible work runs without waiting for anyone. Who decided, and why, is kept beside the action.
AugmentationMore done
by the same humans, because the machine takes the volume and the person keeps the judgement. The time it frees goes to the bigger picture, and nobody is replaced to pay for it.

ALOS brings the work together: humans, AI agents and workflows in one collaborative workspace.

humans

AI agents

Nothing here runs until a person says so, and the decision is written down with their reason, on the same record as the work.

workflows

Integrations

Works with the tools your team already uses

What you can do

Two rules, and the rest follows

Activity
- Opened a changePriya NatarajanPerson
- Proposed a deployBuild agentAgent
Everything is written down
Every action is taken by a named AI agent or a named human, on one sealed record, so a later edit would show and nobody has to trust a summary.
Nothing here runs until a person says so, and the decision is written down with their reason, on the same record as the work.
Nothing goes live on its own
AI proposes. Deploying, merging and publishing wait for a named person, on the same record as the work. Reversible steps never wait.

What you can point at

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 asks a person by name.

Deploying, merging, publishing, sending something to a customer and changing how data is stored wait for a named person
The approval sits beside the work it approved
A refusal is recorded as carefully as a yes

Approvals

An audit trail, for organisations that need one

The record is the product, not a report generated afterwards. It is written as the work happens and sealed as it lands.

Who changed this, and when
Which model was used, 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 it too

Audit trail and evidence

Only what you approved

Your project runs on a list you agree to: the models, the packages, the tools. Anything not on it has to be asked for.

Checked when it is used, not promised in a policy
A complete parts list, with versions and licences

Scans and approved packages

The features

One feature, one page, one job

The humans

Train the humans who run your AI agents

AI Solutions Specialist is a registered apprenticeship, and apprentices learn it by doing real work on real projects beside a mentor. They move on by showing what they can do rather than by serving out the months, and their hours and their sign-offs land on the same record as the work.

AI Solutions Specialist

Competency-based

See the apprenticeship

Who we are

Who we are, and what we are for

TEKIMAX is a Fort Worth software company that builds AI systems for teams who answer for their work. The machine can now do real work, and most tools built around it take the person out of the loop. Then nobody is answerable, and capability without accountability is not progress.

Our mission is augmenting human performance, and it was long before this technology arrived. Not AI replacing a person, nor a person supervising a machine, but the two fitted so each does what it is best at. The idea was argued in 1960 and built on for decades since, and we build in that tradition.

The obvious objection is that a person in the loop is a bottleneck. It is, 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 person. A team gets bigger work done, not smaller, and can show who decided what a year later.

Which way in

Three ways in, three kinds of buyer

The same platform, described three ways, because the person who signs for it is a different person each time.

What it costs

Governance is not the expensive tier

The rules, the record and the approvals are in every plan. What changes is who it is for and how much of it you run, so what it costs depends on the work. Tell us what you are building and we will tell you.

Tell us what you need

Proof and questions

The things humans ask first

Is this a black box with a report on the front?
No. You can look inside it at any point: what is being made, what it is made from, who signed for each step, and where it stops if something is wrong. Each step's kind is decided in advance, from a written list, checked against your rules, and written down.
Who owns what you build?
You do. The solution is yours, and so is the source, the parts list, and the record of what was built and approved. Take all of it to another firm and they can carry on. The platform we build it with stays ours: you are paying for a solution, not a subscription.
What happens to our prompts and our code?
The model providers we send your work to are set to keep none of it, for every organisation, automatically, and what we store is deleted on a set schedule. It is how an account is built, not a switch somebody has to remember. Bring your own provider key and that key runs on your own contract with them, which is worth knowing rather than assuming.
Can we bring our own models?
Yes. A project runs on a list of models you agree to, and that list can be your own provider keys, or a model running on your own machines. What does not change is that the choice is written down and checked when a model is used.
Who is this a good fit for?
Any organisation that has to govern what its AI may do, measure what it did, and show a board or an auditor how its software was built and what is inside it.