IRA tests every control, on every transaction.

IRAME is agentic AI for audit, SOX and finance controls. Its AI, IRA, tests controls on every transaction, so your team reviews results instead of sampling. Internal audit tests the full population and tracks findings to closure. Controllers run SOX and ICOFR testing. Finance teams get IRA inside AP, AR, the close and reconciliation, plus AI-led dashboards for the MIS. A person approves every action.

IRAME is agentic, not a chatbot. ChatGPT and Copilot answer a question about your data once. In IRAME, you describe a control in plain English, GenAI builds the test and IRAME saves it. IRA then re-runs it on the full population on schedule, routes each exception to an owner and tracks it to closure. Same data, same control, same result, with evidence your auditor can re-perform.

IRAME runs AI-led SOX and ICOFR testing, mapped to COSO 2013. IRA, IRAME's AI auditor, runs the test of design, defines the population and tests operating effectiveness on the full population where the data allows. Where the auditor needs a sample, IRA proposes one and documents the method. Your team signs off, and the evidence lets your external auditor re-perform the test under PCAOB AS 2201.

IRAME tests every transaction in the period against each control. That is full-population testing. Sampling picks a few items and infers the rest, so a duplicate payment or split invoice can sit unseen between the picks. Full-population testing finds every exception in the data. IRAME then sorts each one as a true exception, business as usual or a false positive, so auditors focus on what matters.

IRAME deploys three ways: in IRAME's cloud, privately in your own cloud tenancy, or on-premise with on-premise AI models. When IRAME runs in your environment, your data stays there. Controls, reports and Action Hub work the same in each option, and customer data never trains a model in any of them.

IRAME setup starts with one process and one export or read-only connection. IRAME proposes a starting set of controls from past deployments and your own RACM. IRA runs them on your data and your team reviews the results. Most teams see their first exceptions within weeks, not quarters. More processes follow once the first results are agreed.

IRAME never uses customer data to train models. It calls enterprise model endpoints, such as Azure OpenAI, deployed in your region under terms that exclude customer data from training. On-premise deployments use on-premise models. Prompts, data and results never improve anyone's model. IRAME is SOC 2 Type II audited and ISO/IEC 27001:2022 certified.

IRAME's AI, IRA, never acts without a human. It cannot start a workflow, send a message, post an entry, approve or release a payment on its own. A person approves each control before it is saved and reviews each finding before it is reported. Controls run as saved, deterministic logic, so the same data and control give the same result every time.