Audit documents faster when you know where to look.

Find critical clauses, verify evidence, and trust every conclusion — with AI as your audit assistant, not your decision maker.

🔒 Runs in your Azure tenant 🛡️ GDPR by architecture ⚡ Source-traced findings
"Our compliance team spends three weeks on an audit that should take three days. Two reviewers can read the same contract and reach different conclusions — and we still find inconsistencies six months later."
faster than manual
document review
100%
findings traced to
source passage
0
retraining or schema
changes required
The Solution

A verification engine built for real complexity.

Not a search tool. Not a summarizer. A structured, multi-stage reasoning system that checks your documents the way a senior analyst would — systematically, consistently, and with a complete audit trail.

Define criteria in plain English. The system checks every document, cross-references between sources, and produces structured findings with the exact passage that justified each conclusion — defensible, exportable, and ready for legal or compliance review.

Natural-language criteria Multi-stage verification Full traceability Azure-native No retraining

Architecture Overview

📄

Your Documents

PDF, Word, Excel, email and SharePoint — ingested directly from your existing storage

🧠

Knowledge Layer

Azure AI Search · Azure AI Foundry · artifact graph with hybrid vector + keyword retrieval

⚙️

Verification Engine

Proprietary orchestration framework — multi-stage pipeline with cross-document reasoning

📊

Delivery

Azure Functions · Azure AD · Word / Excel export · Structured review UI in your tenant

See It In Action

From 240 contracts to structured findings in under 4 hours

Watch the Audit Assistant process a supplier contract portfolio against 18 compliance criteria — including cross-document checks against attached financial schedules. Every finding traced to its source passage.

Core Capabilities

Four capabilities. One document corpus.

Every capability is built on the same underlying knowledge layer — deploy one use case and expand without rebuilding the foundation.

📋

Criteria-driven document audit

Define audit requirements in plain English — no schema, no coding, no vendor involvement. The system processes every document against each requirement, flagging passes, failures, and ambiguities with source evidence for every conclusion.

Natural-language criteria Conditional logic Bulk processing Per-engagement change
🔀

Cross-document verification

Many audit failures hide in the gaps between documents — a figure in a report that doesn't match its annex schedule, a contract clause that contradicts a referenced policy. The system follows these dependencies and flags mismatches explicitly.

Multi-document reasoning Figure reconciliation Contradiction detection Reference chain following
🔍

Structured findings with full reasoning

Findings present status (Pass / Fail / Ambiguous), the source passage, and the full reasoning chain — nothing is a black box. Drill into any finding, verify against the source, override if needed, and export to Word or Excel.

Pass / Fail / Ambiguous Source citation Reasoning chain Word / Excel export
💬

Natural-language document Q&A

Beyond structured runs, reviewers ask ad-hoc questions across the entire corpus: "Which contracts have no liability cap?", "Show every reference to Article 28", "What is the earliest termination date across all suppliers?" — every answer cites its source.

Corpus-wide queries Source-traced answers Aggregation queries Multi-language
The Interface

Built for reviewers,
not engineers.

A rich inspection interface — not a chatbot, not a PDF dump. Every finding is filterable, drillable, and exportable. Built for compliance teams, legal counsel, and audit professionals who need defensible output.

  • Filter findings by Pass / Fail / Ambiguous status
  • Click any finding to see the source passage and reasoning chain
  • Cross-document references shown explicitly with provenance
  • Human override on any finding — your team stays in control
  • One-click export to Word, Excel, or custom report templates
Audit Assistant — Acme_MSA_2024.pdf (18 criteria)
Findings 16 Pass · 2 Fail · 0 Ambiguous
FAIL Criterion 7: Contract must include a GDPR Article 28 data processing agreement or equivalent clause
No data processing agreement was found. Section 12 (Privacy) addresses data handling at a high level but does not meet Article 28 specificity — no reference to processing purposes, data subject rights, or sub-processor obligations.
Acme_MSA_2024.pdf · Section 12, p.8 · Confidence: High
FAIL Criterion 12: Liability cap must be stated and not exceed 12 months of contract value
Clause 18.3 states "liability shall not exceed amounts paid under this agreement" without specifying a time period. Cross-reference with Schedule A shows annual value of £240,000 — cap is unbounded relative to the 12-month threshold.
Clause 18.3, p.14 + Schedule A, p.22 · Cross-document check
PASS Criterion 3: Termination for convenience with minimum 30-day notice
Clause 14.1 explicitly provides for termination by either party with 60 days written notice — satisfying the 30-day minimum requirement.
Acme_MSA_2024.pdf · Clause 14.1, p.11
Getting Started

Running in your environment within one week

No migration. No new platform to learn. The system connects to your Azure environment and your existing document storage.

1

Discovery workshop

We map your audit workflow, document types, and criteria structure. You leave with a concrete pilot scope and proposal.

½ DAY · FIXED FEE
2

Pilot build

We deploy the system on a real sample from your corpus — your actual documents, your actual criteria. Typically 3–4 weeks.

3–4 WEEKS
3

First live audit

Your team runs the first full audit on production documents. We support the review session and refine criteria.

DAY 1 OF PRODUCTION
4

Expand & evolve

Add document types, new criteria frameworks, or additional use cases (proposal review, risk analysis) on the same foundation.

OPTIONAL RETAINER
The Hardest Check, Automated

Cross-document checks that take an analyst an hour — done in seconds.

The system follows references across the entire corpus. A figure in a financial report can be reconciled against its supporting schedule. A clause in a contract can be checked against a referenced policy document. The mismatches that hide between documents are exposed explicitly.

Figures ↔ Schedules Clauses ↔ Policies Annex ↔ Body + multi-document chains

Live example — financial reconciliation

Source 1: Contract.pdf · Clause 18.3 — liability ≤ amounts paid
Source 2: Schedule_A.pdf · Annual value £240,000
Criterion: Liability cap ≤ 12 months of contract value
Result: FAIL — cap unbounded; missing temporal constraint

Every cross-document check shows both sources and the reasoning chain.

Where It's Used

Any workflow where documents are checked against criteria

The system adapts to your criteria — not the other way around.

📑

Contract review

Check every contract in a portfolio against defined clauses, obligations, and risk indicators. Consistent across thousands of documents.

⚖️

Regulatory compliance

Verify policies and procedures against GDPR, ISO, DORA, or bespoke frameworks. New framework? Update criteria, re-run the audit.

🔢

Financial verification

Cross-check reported figures against supporting schedules. Reconcile discrepancies across financial packages and footnote references.

📬

Tender & procurement

Assess supplier submissions against evaluation criteria. Every bid reviewed consistently, with a documented reasoning trail per decision.

🔎

Due diligence

Review large document collections during M&A or investment processes. Identify missing documents, inconsistencies, and red flags.

📋

Internal policy audits

Verify operational documents remain aligned with current standards. Flag outdated clauses or missing mandatory sections across the organisation.

Why It Matters

Real impact on audit and compliance productivity

Faster than manual review

What used to take three weeks of compliance team effort now takes a few hours — with consistent results across every reviewer and engagement.

100%
Source-traced findings

Every output cites the exact passage that produced it. No hallucinations, no invented clauses — every conclusion is defensible.

Criteria changes per engagement

Update criteria in plain English for each new audit. No schema migrations, no retraining, no vendor involvement to change requirements.

Common Questions

Straight answers

How accurate is it? Can we trust the findings?+
The system is designed to be conservative. When evidence is ambiguous or missing, it flags rather than guesses — you see an "Ambiguous" status with an explanation, not a false pass. Every finding cites its exact source passage. You are always in a position to verify or override any output, and the reasoning chain is visible for every conclusion.
Our audit criteria changes every engagement. Does that require reconfiguration?+
No. Criteria are defined in plain language at the start of each audit run — as a document or structured input. Changing requirements for a new engagement is as simple as updating that input. No code changes, no vendor involvement, no retraining. This is a core design principle of the system.
Our documents contain highly sensitive data. How is it protected?+
Everything runs within your Azure tenant. Documents are processed by your Azure AI Foundry deployment — no data is sent to external APIs. Your existing Azure AD access controls, DLP policies, and data residency settings apply from day one. We provide a Data Processing Agreement for your procurement and legal review.
Can it handle our document volumes and formats?+
Yes. The serverless architecture scales on demand — volume is not a constraint. The system accepts PDF, Word, Excel, email, and plain text. For very large corpora (thousands of documents), we design the pipeline architecture to process in batches with progress tracking and resumability.
We already have a compliance team. Why do we need this?+
This system does not replace your compliance team — it eliminates the work that should not require human expertise. Reading the same clause across 300 contracts is not judgment work. Finding the three that deviate is. Your team spends their time on the cases that actually need human judgment, not on the bulk review work that precedes it.
How long does a typical deployment take?+
A pilot using a real sample of your documents typically takes 3–4 weeks from kickoff. This gives you a working system on your actual data, with your actual criteria — not a demo. Full production deployment, if you choose to proceed, typically follows within 4–6 additional weeks depending on integration requirements.
Ready to see it working?

Run it on your documents.
Not on a slide deck.

The best way to evaluate this system is a live demo on a real — even anonymised — sample from your actual workflow. Book a 30-minute call and we'll show you a live run, then tell you honestly whether your use case is a fit.

No commitment · No slide deck · Engineers talking through your problem · Based in Switzerland, operating across EU & UK