dnl Audit Platform Reviews & Product Details

dnl: the AI-powered audit platform for disclosure checking, number verification, and report review Who we are dnl (DNL Deep Neuron Lab) builds an AI-powered audit platform for external auditors. Berlin-based and used by more than 13,000 auditors worldwide, we focus on the most time-consuming and inspection-sensitive parts of the audit: completing disclosure checklists, verifying the numbers in financial statements, surfacing findings, and reviewing audit reports. The dnl platform is built for how audit teams actually work: structured, evidenced, and ready to stand up to regulatory inspection. The dnl platform is used by firms including KPMG, BDO, RSM, Forvis Mazars, Baker Tilly, Moore, HLB, Nexia, CLA, and dhpg, as well as reporting teams at organisations such as Porsche. We are active across Europe and the UK, including partnerships with Mercia and the IFRS Foundation on the disclosure checklists in the platform (FRS 101, FRS 102, FRS 105, IFRS, and sector-specific frameworks), and are expanding into North America, with a US GAAP disclosure checklist now available. What we do Disclosure checking (ai/checklist). Working through a disclosure checklist manually takes days and produces a document trail that inspectors will scrutinise line by line. ai/checklist analyses financial statements against the applicable disclosure requirements, whether IFRS, UK GAAP (FRS 101, FRS 102, FRS 105), US GAAP, or ESG frameworks (ESRS, ISSB, GRI), and flags what's present, what's missing, and what needs judgement. Backed by embedded audit agents, it auto-populates responses to complete around 90% of validations in real time, surfacing only the judgement calls that need a human. Every conclusion links back to the specific page and passage in the financial statements, so the evidence trail is built as you work, not reconstructed afterwards. Firms can also bring their own proprietary checklists and methodologies. Number checking (ai/numbers). Financial statements are full of numbers that must agree with each other: totals, cross-references, prior-year comparatives, notes that tie to primary statements. ai/numbers uses evidence agents to tick-and-tie in seconds, running mathematical-accuracy checks alongside internal, external, and prior-year consistency reviews. It flags the few numbers that don't match, and confirms the thousands that do, so the team spends time investigating genuine discrepancies rather than ticking numbers that were always going to agree. It works across structured and unstructured formats, including Excel, PDFs, and report tables. Findings (ai/findings). ai/findings captures and structures audit findings the moment they emerge, as the engagement progresses, so they're organised and ready for the report. No more hunting at the end of the cycle for what was flagged along the way. Report review (ai/report-review), now live. ai/report-review lets teams self-check audit reports before they reach the central review team, catching issues early and submitting with confidence. Each quality check comes with a clear explanation behind the AI's judgement, so it's obvious what's working and what needs a second look, meaning smoother reviews, fewer surprises, and less back-and-forth. Coming soon. ai/accounts turns messy charts of accounts into clean, audit-ready financial statements with AI-driven mapping to the balance sheet and P&L. What makes us stand out Built for auditors, not adapted for them. The dnl platform isn't a general-purpose document tool with an audit use case bolted on. Disclosure requirements, checklist logic, and the evidential standards of audit inspection are the foundation of the product, not a feature layer. The platform is configured around each firm's own methodology, checklist structure, and review patterns. Every output is traceable. Regulators are clear that the auditor remains responsible for conclusions regardless of what technology was used to reach them. The dnl platform is designed around that principle. Nothing is a black box: every check, flag, and extraction links to its source, so the workpaper explains itself. Inspection-ready by design. The FRC's annual inspection reports return to the same themes year after year, and disclosure completeness is a recurring one. The dnl platform's workflow produces documentation that answers the questions inspectors actually ask, with a complete, automatically recorded audit trail. Professional scepticism stays with the professional. The dnl platform handles the mechanical work of matching, checking, and cross-referencing, so auditors can concentrate on the judgements that require experience. Every AI suggestion is reviewed and confirmed by the auditor before it's accepted. The platform accelerates the audit; it doesn't attempt to replace the auditor. Security and data handling Security is built into the core product, in line with the audit-grade accountability the platform supports. dnl is ISO/IEC 27001:2022 certified and GDPR compliant, with data encrypted in transit and at rest and access tightly controlled. Your data is hosted in your own region, whether the EU/EEA, the US, or Australia, and customer data is never used to train, fine-tune, or improve our models. Who it's for Audit firms of all sizes, from teams looking to eliminate the checklist grind to firms responding to inspection findings on disclosure quality. Used across financial audit and ESG/sustainability audit, by partners, engagement auditors, and innovation leads alike. If your busy season involves late nights ticking and tying, the dnl platform was built for you.