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AI Regulatory Document Generation Services
Ailoitte is a regulatory document automation company. We build AI that writes first drafts of clinical, submission, device and quality documents from your own data and templates. Each statement links back to its source. Each action is logged for Part 11. And a qualified writer signs off every page. The draft is automated. The accountability is not.
Tell us the document, your markets and where time is lost. Within a week: whether it is a good fit, what QA will need, and the fixed price.
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Traceable to source
Each line links to the data behind it.
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Affordable by design
Fixed price from $4,000 per document type.
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Validation-ready
We hand over the proof QA needs.
AI regulatory document generation, in six answers.
What it drafts
Trial documents, filing content, device files and quality records. It writes them from your own data, your templates and past approved work.
Who stays accountable
Your writers. They check, fix and sign every page. Their job moves from writing first drafts to making them better.
How long it takes
A pilot for one document type in 4 to 6 weeks, and several types in 10 to 16. Your QA work runs alongside from week one.
What it costs
A fixed price per document type, from $4,000 to $39,000 by scope and AI use, quoted after a free audit. No fee per page or per filing.
How it is validated
We build it to be validated and hand over a CSA-aligned evidence package. Your quality assurance team performs and owns the validation.
What you keep
The code, prompts, settings, test sets and proof pack are yours once paid. Your data and drafts stay in your own systems.
Sunil Kumar 
What automated compliance document generation is, and where accountability sits.
AI regulatory document generation writes first drafts of regulated documents from your own data, templates and past work, then sends them to a qualified person to review. A team of AI agents does the slow, repetitive part. It finds the right data, follows the template, keeps cross-references and numbers right, and flags anything that does not match before a person reads it.
Regulators treat help with writing differently from AI that shapes a decision. FDA’s January 2025 draft guide on AI in drug work sets out a seven-step test of trust. It leaves out tools that save time without touching patient safety, drug quality or study results (Goodwin, on the FDA draft guidance). In January 2026, EMA and FDA added ten shared principles for good AI practice. They rest on human oversight, a defined context of use and risk-based validation (RAPS).
Either way, the sponsor still answers for every word it files. That is the core of our AI regulatory document generation services. Your writers stay the named authors. The system just gives them a draft they can trace and improve, in place of a blank page.
Which document eats your calendar?
Send one example with names removed. We will tell you how much of it repeats, and how much of the drafting we could take off your team.
Two kinds of regulated writing
Clinical and submission documents, or device and quality records?
Both are strict, structured and repeated often. But they answer to different rules and different reviewers. Drug makers, CROs and biotechs often start with trial documents. Device makers often start with quality records, where the shape repeats most and the payback comes first.
Track 01
Medicines: clinical and submission documents
The problem: a fixed filing date and too few writers.
- Protocols, brochures for trial sites, study reports
- Patient narratives and CTD filing sections
- ICH guidelines and EU GMP Annex 11 apply
- Hundreds of links between sections to keep right
- Success: days from final data to signed draft
Track 02
Devices and quality: technical and quality records
The problem: the same structure, rewritten by hand.
- Technical files and safety follow-up reports
- Deviations, CAPA records and SOPs
- EU MDR, IVDR and ISO 13485 apply
- Same shape each time, so quick to pay back
- Success: fewer review rounds and fewer errors
What changes
Regulated authoring, before and after automation.
The problem is rarely how well people write. It is the slow work around the writing, and the weeks it eats.
| Step | Today | With automated drafting |
|---|---|---|
| The first draft | Senior writers piece it together by hand from tables and old files. | A draft arrives with every line linked to its source. |
| Cross-references | Hundreds kept by hand, and errors show up at review. | Kept in sync and checked again each time the draft is rebuilt. |
| Source data changes | Each linked document found and fixed by hand. | The sections it touches are flagged and redrafted for the writer. |
| Review | Reviewers spend their time on numbers and wording. | Reviewers spend their time on science and risk. |
| Inspection | Working out who wrote what, from which data, takes days. | The log shows the source, the model, the writer and who signed. |
How it works
Inside a multi-agent drafting system, step by step.
Four steps, and the last one is the point. In a filing, a claim with no source is a finding, not a typo. So the system flags a gap instead of making text up. And a qualified writer signs every section before it becomes a record.
Step 01: Retrieve
- Only from your source of truth
- Tables, reports and past filings
- Never from what the model knows in general
- Gaps flagged, never filled
Step 02: Draft
- Your templates and house style
- One agent per type of section
- A source link on every claim
- Model and prompt version recorded
Step 03: Check
- Links and numbers checked
- Anything that does not match is flagged
- Terms kept the same throughout
- Refusal tested before any pilot
Step 04: Route to a writer
- A named writer reviews every section
- Edits and reasons captured
- An e-signature on approval
- Nothing submitted without sign-off
Coverage
Measure my baseline
AI regulatory writing software development, by document type.
Each type needs a structured template, a defined source of truth, and enough precedent to learn your house conventions. Final eCTD publishing and submission checks stay with your publishing team.
Clinical trial documents
Protocols, site brochures, study reports and patient narratives. For most sponsors, this is the biggest writing load.
Submission components
Content built to the CTD layout, with links and numbers kept right from one section to the next.
Device technical files
Technical files, clinical evaluation reports and safety follow-up reports under EU MDR and IVDR.
Quality records
Deviation reports, CAPA records and test summaries. The shape repeats, so they often pay back first.
SOPs and work instructions
Drafted and updated when your process changes, with each change traced and signed.
Responses to regulators
Draft replies to questions from regulators, based on what you filed and earlier letters.
How many writer hours go into first drafts?
Send the document types, how many you write a year and your team size. We will measure your own baseline in the audit.
How we deliver
From document audit to a validated pilot, in five stages.
A pilot for one document type in 4 to 6 weeks, and several types in 10 to 16. Your QA team’s work is planned in from week one, not left as a gate at the end. Delivered on Clarity, our delivery method.
Stage 01
Document audit
We review your documents, templates and data. We find what truly repeats, where link errors happen, and how long drafts take today.
Stage 02
Risk classification
We define what each function is for, give it a GAMP 5 class and a risk level, agree the test scope with QA, and map where Part 11 applies.
Stage 03
Agent architecture and build
The agents read from your trusted data, follow your templates and house style, and log every step from the first line of code.
Stage 04
Test on past submissions
We draft from old source data and compare the result with what was approved. We check that gaps get flagged, and sort errors with your writers.
Stage 05
Pilot and hand over
One live document type with full human review. We measure results against your baseline and build the proof pack for QA. Then you decide go or no-go.
The first question QA will ask
The software itself is a GxP system, so it must be validated.
If a partner has not raised validation before you did, that is a warning sign. We raise it in the first call, sort each function by risk, and build so your QA team can sign it off with the proof we hand over.
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01
Validation is required
Software used in making a product or running the quality system must be tested for the job it does. For US devices, the quality rule has matched ISO 13485 since 2 February 2026 (IntuitionLabs). For medicines in Europe, EU GMP Annex 11 applies.
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02
Computer Software Assurance
FDA made its Computer Software Assurance guide final in September 2025. It replaces long scripted tests with checks sized to the risk, and it includes a cloud software example (Kneat).
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03
Proportionate, not uniform
A drafting function carries different expectations from one that writes to a regulated record. We classify every function by risk at design time, so the assurance scope is known before the build.
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04
What we deliver, and what stays yours
Intended use statements, risk classification, design and configuration specifications, test evidence, a traceability matrix and change records. Your quality assurance team performs and owns the validation.
Data integrity
Drafts your quality team can trace, attribute and reproduce.
We design against 21 CFR Part 11, EU GMP Annex 11, ICH Q9 and Q10, GAMP 5 Second Edition and ALCOA+, and your quality assurance team confirms which apply. See security and compliance and private AI deployment for systems that must run entirely inside your own tenancy.
Grounding
- Drafts built from your sources only
- Gaps flagged instead of filled
- Only document types your data supports
- Refusal tested before any pilot
Traceability
- A source link on every claim
- Links checked again on every rebuild
- Model and prompt saved per section
- The same inputs give the same output
Part 11 records
- A log of who, what, which source and when
- Attributable electronic signatures
- Role-based access control
- Records kept and easy to find
Inspection readiness
- ALCOA+ data integrity by design
- Proof exported in one step
- IQ and OQ documents supplied
- Rule mapping reviewed each year
In production
View Portfolio
Regulated documentation we already automate.
Compliance records and clinical notes share the hard parts of regulated writing: strict templates, a defined source of truth, a complete audit trail, and a qualified person who signs. See ROI case studies.
Pricing
What automated compliance document generation costs.
A document type costs $4,000 to $39,000, fixed, based on scope and how much AI it needs. A quality record with a stable template sits near the low end. A study report that pulls from many data sources, with DMS links and private hosting, sits near the top.
The price moves with the number of sources, templates and markets, and how much proof QA needs. Running costs such as AI use and hosting are listed on their own. Larger programs can run as an AI Velocity Pod from about $15,000 a month.
Integration
It writes into the systems your regulatory team already runs.
Drafts land in your document system with tags and sign-off steps in place. Your writers do not need to check a second tool.
Document management
Veeva Vault, MasterControl, Documentum or SharePoint, set up per project.
eTMF
Trial master files, with tags and sign-off steps kept in place.
Clinical data
Tables and figures from your statistics team.
Publishing
Clean content passed to your eCTD publishing tool.
E-signatures
Part 11 sign-off steps with named signatures.
Quality system
Deviation, CAPA and change records.
AI models
Your choice of provider, set never to train on your data.
Your own tenancy
Open models in your cloud or on site when data cannot leave.
FAQ
Ask a regulated AI lead
AI regulatory document generation, answered.
What are AI regulatory document generation services?
Building a system that drafts regulated documents from your own source data, templates and precedent, then routes them to qualified reviewers. Agents retrieve the data, apply the template, keep cross-references consistent and flag gaps. Your writers review, correct and approve.
What does a regulatory document automation company actually deliver?
A working drafting system, its audit trail, and the evidence package your QA team needs to validate it. We build into your document management system and hand over code, configuration and test sets, so your team can run it without us.
Does the AI replace our regulatory writers?
No. It replaces the blank page and the mechanical assembly work. Writers move from producing first drafts to reviewing and improving them, and remain the named, accountable authors.
Does the software itself need to be validated?
Yes, if it is used in production or the quality system. It is a GxP computer system and must be validated for its intended use. We build it to be ready to validate and deliver the evidence package; your quality team performs and owns the validation.
What is Computer Software Assurance and how does it apply?
FDA’s risk-based framework for assuring production and quality system software, finalized in September 2025. It replaces exhaustive scripted testing with assurance proportionate to risk, so a drafting function needs less than one that writes a regulated record.
How do you stop it inventing content or citations?
Grounding, traceability and refusal. Statements come only from your source documents, each carries a link back to its data, and the system flags a gap rather than filling it. We test that deliberately before any pilot.
Is it compliant with 21 CFR Part 11?
It is designed for Part 11 from the start. Every generation event is logged with user, time, source and change reason, approvals carry attributable electronic signatures, and we supply IQ and OQ documentation to support your validation.
Which regulatory frameworks do you design against?
21 CFR Part 11, FDA CSA and device quality rules in the US; EU GMP Annex 11, EU MDR and IVDR in Europe; ICH Q9 and Q10, GAMP 5 Second Edition and ALCOA+ across both. Your quality team confirms which apply.
Which documents can it draft?
Clinical, submission, device and quality documents. Protocols, investigator brochures, study reports, patient narratives, CTD module content, technical files, clinical evaluation and surveillance reports, deviations, CAPA records, validation summaries and SOPs.
Can it handle eCTD structure?
It generates content aligned to CTD module structure and keeps cross-references consistent. Whether it writes into your publishing tool or hands off structured content depends on the tool, and final submission validation stays with your publishing team.
Will it integrate with our document management system?
Yes. We build integration with Veeva Vault, MasterControl, Documentum, SharePoint and eTMF platforms, so drafts arrive with metadata and approval workflows intact. Each connector is scoped per project.
How long does implementation take?
A working pilot for one document type in 4 to 6 weeks. Several document types take 10 to 16 weeks, with your validation activities planned in from week one.
How much does AI regulatory writing software development cost?
Between $4,000 and $39,000 per document type, fixed, depending on scope and the AI involved. Running costs such as AI usage and hosting are listed separately. We quote after a free document audit.
Do you publish accuracy percentages?
No, and be cautious of vendors who do. Accuracy depends on your document type, source data and templates. We measure your baseline in the audit and report against it during the pilot, with the method stated so QA can assess it.
Can it run entirely on our infrastructure?
Yes, and in this sector it often must. We deploy open models inside your tenancy or on-premise, so no regulated content leaves your environment, and your content never trains outside models.
A question from your QA or regulatory team?
Send it over. A regulated AI lead replies within 12 hours.
Give your writers a traceable draft, not a blank page.
Tell us the document type, your submission markets and where the calendar is lost. A senior architect will tell you whether it is a good candidate, what the assurance scope looks like, and which document types we would leave alone.
- Mutual NDA before we see any regulated content
- A regulated AI architect on the call, not a salesperson
- A free document audit and fixed price within a week
- No obligation, and nothing to pay to find out
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