AI for compliance
Compliance review that is faster, consistent and auditable
We build AI systems that check documents against a regulation and your own policies, score the gaps and draft the remediation. We have one in production with Saudi banks.
Technology we use for this work
The problem
Manual review does not scale, and inconsistency is a finding in itself
Banks, insurers and healthcare organizations must show that policies, contracts and notices meet data protection law. Manual review is slow, and two reviewers often reach two different answers on the same document.
An AI reviewer only helps if its findings are traceable to the clause and the article, its accuracy is measured, and a qualified person makes the final call. We build all three into the system.
What we build
What does our AI for compliance service include?
Document review against regulation and your internal framework, gap scoring and drafted remediation with human sign-off.
Regulation and policy knowledge base
The law, guidance and your internal policies structured into a knowledge base the review engine retrieves from.
Document ingestion including scans
PDF, Word and Excel ingestion, with vision OCR for scanned files, so paper-era documents are reviewed with the same rules.
Gap scoring against the law
Findings scored against the regulation and your internal compliance framework, and summarized in an automatic gap report.
Remediation drafting
A pipeline that drafts compliant replacement text for the gaps found.
Cost-aware model routing
Several open-weight models routed by task, balancing accuracy against cost.
Compliance chat agent
A multi-agent assistant with tool calls, so compliance staff can question documents and the regulation directly.
Architecture
How does it work, step by step?
-
Ingest
Documents
- PDF, DOCX, Excel
- Vision OCR for scans
- Classification
-
Evaluate
Review against law
- Retrieval over regulation
- Scored against law and policy
- Gap report
-
Remediate
Draft fixes
- Compliant replacement text
- Drafted per gap
-
Assist
Chat agent
- Multi-agent with tool calls
- Questions about documents and law
- Findings linked to the clause reviewed and the requirement it was tested against
- Scoring accuracy measured on your own documents before it is relied on
- Open-weight models available where documents must stay in an approved environment
- A qualified person approves remediation before it is used
Proof
Where have we delivered this?
An AI compliance platform for Saudi PDPL, live with banks
A platform that reviews client documents against the Saudi Personal Data Protection Law, scores the gaps and drafts compliant replacements, now in production with banks and finance companies.
Result: 95% content fidelity on AI-drafted documents
Read the case studyGoverned BI and a financial data platform for banking and insurance
Semantic layers, a governed financial warehouse and BI across five business units, with strict access control and automated report distribution.
Result: 50% faster dashboards on insurance BI
Read the case studyPlain-English questions against a governed life sciences database estate
A natural language analytics service for a commercial intelligence platform used by medical and field teams at global pharmaceutical companies.
Result: Read-only by policy: the pipeline cannot produce a write
Read the case studyContext
Industries and related services
Industries
Related services
FAQ
AI for compliance: common questions
Which regulations can this be applied to?
Our production system reviews documents against the Saudi Personal Data Protection Law (PDPL). The same approach can be applied to GDPR, HIPAA privacy requirements and internal policy frameworks, because the regulation lives in a knowledge base rather than in code.
Does the AI make compliance decisions?
It should not. The system finds gaps and drafts fixes; responsibility for compliance stays with your team. In new builds we design an explicit approval step so a qualified reviewer signs off remediation before it is used.
How accurate is it?
On our PDPL platform, generated documents reach 95 percent content fidelity on our evaluation set. We measure accuracy per client on their own documents during the assessment before relying on it.
Can it run without sending documents to a third-party AI provider?
It can be designed that way. Our production system uses five open-weight models balanced by accuracy and cost. Where documents must not leave your environment, we serve open-weight models inside it; we agree the deployment model during the assessment.
Is Involabs itself certified?
We do not hold a company certification such as SOC 2 or ISO 27001. We design systems to align with the requirements of HIPAA, GDPR and Saudi PDPL, sign NDAs, and document our controls on our Security and trust page.
Start with a two to three week assessment.
Send us the problem and the constraints. You get a written architecture, a risk register and a costed roadmap, and you keep them whatever you decide next.