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A Standard File is the authoritative reference document you upload that defines the criteria, controls or clauses you want to assess against (e.g. a published standard, internal policy manual, or regulatory guideline). ComplyIQ360 parses this file so your other documents can be automatically benchmarked against it. You must ensure that you have the appropriate usage right of the standard file that you upload.

A Report File is any document (like a draft policy, procedure, or disclosure) you want to assess against the Standard File. The platform analyses gaps and generates a report summarising its alignment.

Any text-based, clause-structured PDF in English. Examples include ISO standards, regulatory guidance, internal policies, supplier codes, and ESG frameworks. If it's structured with sections or numbered items, it will generally work. You must provide your own standard file.

PDFs provide a consistent layout and text extraction pipeline, reducing ambiguity in structure. Other formats introduce variability that can degrade accuracy. For now, please export your documents to PDF before uploading.

Patch analysis lets you upload a new or updated report after a full analysis, so ComplyIQ360 can update the compliance result without rerunning the whole job. It is designed for focused updates, such as fixing specific gaps or adding missing evidence. The system automatically detects new pages and can analyse up to 20 new pages per patch. Patch analysis is currently free and may be used up to 3 times per job, but because it only analyses the update in context, it may produce a less complete result than running a fresh full analysis.

After a compliance analysis is complete, you can chat with the analysis to explore the organisation’s processes, controls, roles, evidence and gaps. The chat is grounded in the compliance analysis and the uploaded resources, so it can answer questions such as what a gap means operationally, which controls appear weak, what evidence may be needed, and how to fix a gap safely without accidentally weakening other requirements. It is intended as compliance-focused decision support, not general-purpose chat or legal advice.

General chat tools usually give quick, broad answers. ComplyIQ360 runs a deeper, multi-stage compliance pipeline: it extracts requirements, analyses uploaded report evidence, checks gaps, and generates traceable outputs. This deliberate process can take longer, but it supports more detailed clause-level analysis and evidence references.

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The job continues on our servers. When it finishes, results are stored and accessible from the Job History section of your dashboard. Closing the tab does not cancel processing.

Use patch analysis when you have made a small, focused update after reviewing the original result, such as adding a missing policy page, correcting a disclosure, or uploading evidence for a specific gap. Use a full analysis when the report has changed substantially, when more than 20 pages are new, or when you need the most complete and reliable assessment across the whole document set.

Yes. If a job terminates in a system error state (not user-cancelled), the consumed credit is automatically returned to your balance.

Organisation credits are always consumed before your personal credits when you run a job under that organisation’s context. The platform automatically falls back to your personal balance if the organisation's balance is exhausted.

Other members of your organisation do not see your jobs listed in their own history, so they can't browse or discover your job IDs. If you choose to share a job ID with someone, only members of the same organisation can use it to open the result or chat with it — people outside your organisation cannot access it even with the ID. In short: job IDs aren't exposed to other members automatically, and sharing one only grants access within your own organisation.

All customer-uploaded files and generated outputs are stored securely in AWS Sydney (ap-southeast-2). Our current production workflow performs AI inference through AWS Bedrock-hosted models from our AWS-hosted backend. Customer files, prompts and outputs submitted through this workflow are not used to train foundation models. When you delete a job, the primary uploaded content and generated output are removed, while limited metadata may be retained for usage, billing, audit and security purposes.

No. The current ComplyIQ360 production workflow does not directly route customer files to separate external AI provider API accounts. Compliance analysis is performed through AWS Bedrock-hosted foundation models from our AWS-hosted backend, with persistent files and generated outputs stored in AWS Sydney.

No. Reports are analytical decision-support tools highlighting textual compliance gaps. Always have qualified professionals review and finalise interpretations before regulatory submission or contractual reliance.