AI governance documentation services leave you with files an auditor, a customer or a regulator can read without calling us. As a Dhaka-based company, we write them for international companies, one AI system at a time, at a fixed price: an inventory of every AI system, a risk register with owners and controls, policies written for how your teams actually use AI, and review evidence. A documentation lead and an engineer read your systems inside your own document system, and your named owner approves every page.
One exit at each step. No long-term commitment at any of them. We start with the AI system that would embarrass you first in an audit: the chatbot nobody registered, the vendor model with no owner, the scoring tool a customer questionnaire just asked about. What exists is inventoried, the gaps against the framework you are measured on are listed, and the first pack is defined and costed in your numbers.
You get a written verdict — an inventory first, one system’s governance pack, a policy set with owners, a law-specific pack instead of a generic one, or a quarterly review over what already exists. If nothing justifies a pack, you stop here and keep the gap review.
AI governance documentation services produce six documents that show how your organisation controls its AI: an AI inventory, a risk register with owners and controls, a policy and procedure set, a mapping to the framework you are measured on, approval records, and a routine that keeps them true. The deliverable is files an assessor can read.
Every AI system and use case listed with purpose, users, data, vendor or model, version, owner and status, so “which AI do we use?” takes a minute, not a meeting.
Each system’s risks with likelihood, impact, a named owner, the control against it and the review date, in plain language your risk committee accepts.
An acceptable-use policy, a development and procurement procedure, a human-oversight rule and an incident procedure, written for how your teams use AI, approved and dated.
Each document tied to the clauses of the framework you are measured on, so a gap is visible before an assessor finds it; mapping is documentation work, not a certification.
Who approved which document, when, against which version, and what changed since: the records that turn a policy into proof.
A review calendar, a change procedure and a handover session, so your own team keeps the files current as systems, vendors and rules change.
Every AI governance documentation pack is built from four documents, and the gap review says which you lack first. The inventory says what AI exists; the risk register says what could go wrong and who owns it; the policy set says what people may do; the control record says what is in place. All four sit inside our AI services.
A register of every AI system and use case with owner, data and purpose, when nobody can say how many AI tools the company runs.
Risks per system with likelihood, impact, owner, control and review date, when a customer questionnaire or a board asks what could go wrong.
Acceptable use, procurement, human oversight and incident procedures, when staff use AI daily and the only policy is a generic IT rule.
Which controls exist, who runs them, and the evidence they ran, when policies are written but nobody can show they are followed.
An AI governance documentation pilot produces one system’s full pack in four weeks: the scope signed, the inventory entry, the risk register, your owner’s sign-off and the handover. The example is a customer-support chatbot on a vendor model; every item traces to a document version, an approver and a date, and yellow marks where a person signs.
Pilot log · one AI system
The pack at that step · its result
Scope signed
The system, its data and its owner, before any drafting.
Inventory entry
The first record an assessor asks for.
Risk register
Every risk with an owner and a control.
Owner sign-off · a person signs
Your risk owner reviews the whole pack.
Handed over
The pack stays in your own systems.
Click a step, or a number below, to switch the result
Every quarter the owner signs a review record, so the files stay true between audits.
Illustrative example. Click a step to see the pack at that point. Yellow marks where a person signs; every item traces to a document version, an approver and a date.
AI governance services with us run in five steps you can stop between, because governance fails when it is sold as a workshop and a template: a free scoping call, a two-week inventory and gap review, a four-week pilot that writes one system’s pack, production for the remaining systems, then quarterly Managed Ops. Every step ends with signed documents.
A documentation lead who owns the pack and the review calendar, an engineer who reads how each system works, and a reviewer who checks every document before your owner sees it.
The first AI governance documentation depends on which of five situations you are in; five questions decide. No inventory means the inventory first; a few systems and no policies, one system’s pack as the pilot; nobody owning AI risk, owners and a policy set; a specific law, our EU AI Act documentation; everything in place, a quarterly review.
1. How many AI systems or tools are in use?
2. Is there an inventory of them?
3. Who owns AI risk today?
4. What are you being measured against?
5. Do AI-specific policies exist?
A few systems and no policies is the normal starting point: the most exposed system gets a full pack (inventory entry, risk register with owners and controls, the policies that apply, framework mapping and approvals) in four weeks.
A first estimate; the gap review confirms it.
How the verdict is decided
An AI governance documentation company is judged on whether its files survive the first hard question from a customer or an assessor, not on the binder’s thickness. We write registers with owners, policies with approvals and records with dates; where a law such as the EU AI Act is in scope, the files follow its list of required records.
Outsourcing AI governance documentation is safe when access, approval and boundaries are settled first, because the real risk is who sees system details and who signs the documents. As a Bangladesh-based company, we work inside your document system under a non-disclosure agreement, read system descriptions and never production data, and give no legal advice. Reviewed By Eicra.com team
Before you pay for AI governance documentation, you get evidence instead of promises: a two-week gap review that ends in your own written plan, a pilot pack approved by your owner before production is quoted, and a free 30-minute scoping call. Client case studies with numbers are added as clients give permission to name them.
For the AI inventory and gap review, ending in a written plan against the framework you name.
To one AI system’s full governance pack, written with your owner and signed on the last day.
Of free rework when a document fails its agreed acceptance list after handover.
Our AI governance documentation services are priced per outcome, never per hour, and each price is on the price cards at the top: a two-week AI inventory and gap review ending in a written plan, half credited to the pilot; one AI system’s full governance pack, written, approved and handed over; further systems quoted after the pilot.
AI governance documentation services produce the written records that show how an organisation controls its AI: an inventory of every AI system and use case, a risk register with owners and controls, an acceptable-use and oversight policy set, a mapping to the framework you are measured on, and dated approval records. The deliverable is files an assessor can read.
Six, in practice: an AI inventory listing every system with owner, data and purpose; a risk register with likelihood, impact, owner and control per risk; policies for acceptable use, procurement, human oversight and incidents; a control record showing what is in place; approval records with versions and dates; and a review calendar that says when each file is re-checked.
For each AI system: the risk in one sentence, the harm it could cause and to whom, a likelihood and impact rating, the named owner, the control that reduces it, evidence that the control runs, the residual rating, and the next review date. A register that lacks owners or evidence is a list of worries, not a governance record.
Through a review calendar and a change procedure written into the pack: any new AI system or vendor tool is added to the inventory before use, risks are re-rated when a system’s purpose, data or model changes, policies are re-approved when rules change, and every quarter the owner signs a review record. Managed Ops runs that cycle if you want.