Solutions

One Platform.

The complete audit.

Risk Intelligence Engine

Uncover every risk.
Test where it matters most.

Evaluate every transaction, prior periods with 30+ audit control inputs to dynamically score risk across financial statement line items.

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Transaction Scoring

Score every transaction using Machine Learning algorithm.

Anomaly Detection

Identify unusual patterns across accounts and periods.

Automated Evidence Verification by Finspectors

Evidence Automation

Upload evidence. AI verifies it.
You only review exceptions.

Auto extract data, validate transactions against source and find discrepancies in seconds. Every finding is fully traceable to the original document.

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AI-assisted substantive testing with variance detection

Source-linked evidence for every audit conclusion

Exceptions prioritized for faster reviewer sign-off

Defensible audit trail across the entire engagement

smart workpapers

Workpapers that write themselves, based on what you just tested

Instantly generate AI-drafted workpaper conclusions from testing results, findings, and audit assertions. Then review, adjust, and sign off in minutes.

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AI-drafted conclusions informed by testing and risk assessment

Evidence automatically linked to each workpaper

Assertions and findings captured in context

Structured, defensible, review-ready documentation

Document management interface showing categories of assets with expandable lists and templates for accounting tasks such as Cash at Bank, Restricted Cash, Trade receivables, Prepayments, and Property, Plant and Equipment.

Structured client requests, simplified engagement coordination by Finspectors

Client Collaboration

Centralize client communication.
Eliminate the chaos.

Send structured requests to clients and track submissions in real time through a secure portal, with full visibility into what's received, pending, or overdue.

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Request Builder

Customised information requests at click of a button.

Unified Workspace

Clients access to upload documents and respond to queries.

Template library

Choose from our library or customise your own for reuse

Realtime status

Track outstanding or overdue requests with our dynamic dashboard.

Financial Statement Review

Catch every discrepancy,
before sign-off.

AI automatically reviews financial statements for mathematical accuracy, cross-referencing, and prior-period consistency, flagging discrepancies before they reach the partner's desk.

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Automated mathematical and total verification checks

Prior-period comparison across financial statements

Internal consistency and cross-reference validation

Structured discrepancy review with Accept or Ignore workflow

Validate Financial Statements with confidence by Finspectors

Why us?

What sets

Finspectors Apart

Finspectors

Trullion

Where does it start?

Upstream Capability

Starts at materiality, risk, scoping. Downstream agents use those upstream decisions

Enters at fieldwork. Planning, Risk, and materiality are entirely out of scope

Agents vs Chatbot

Agentic AI Claim

6 agents: Workpaper · Request · Risk · Substantive Test · Review · Reporting.

Trulli is a Q&A chatbot. It does not run audit procedures autonomously.

Built for whom

Audit-Native Design

Built by Chartered Accountants with Big 4 experience. Designed for audit, not adapted.

Core product is lease accounting. Audit added in 2024. Accounting-first architecture.

Finspectors

Fieldguide

QC 1000 / ISQM / SQMS

Firm Quality Management

PCAOB QC 1000, ISQM, SQMS - live, tied to engagement data. Not a module. Native to every audit

No quality management layer. Firm-level governance is out of scope

AI / ML Risk Engine

Risk Intelligence

AI/ML scores every GL transaction before fieldwork. Risk is ranked, not sampled.

AI speeds up procedure execution, Does not score the full GL for risk.

DNA

Audit-Native Depth

Built for financial audit by practicing CAs, Audit depth, not advisory breadth.

Spans SOC, advisory, and financial audit. Broad by design, not audit-native

Finspectors

Inflow

Agentic vs Assistive

AI Positioning

Named agents run procedures - Materiality, Evidence Automation, Reviewer, Audit Copilot

Inflo's stated position: assistive only. Not to automate conclusions. By design.

Document-Level AI

Evidence Verification

Upload evidence. AI verifies it. You review exceptions only.

ADA analytics flag anomalies. Document-level verification remains audito-led

AI-Drafted Conclusions

Workpaper Generation

Workpapers generated from evidence and test outcomes. Agent writes, auditor signs.

Workpapers are managed digitally. Content is still auditot-authored

Finspectors

CaseWare

Agentic vs Assistant

Execution Model

Agent generated workpaper, PBC list and report. Auditor reviews and approves

AiDA: open -> ask -> verify -> paste.
Auditor still assembles the output

Workflow Coverage

AI Output Scope

AI produces workpapers, PBC lists, reports, and file-level reviews.

AI produces summaries and narrative only. Core outputs are not AI-generated.

Total cost of ownership

Platform Sprawl

One platform, one contract, one onborading. Everything included.

Full coverage needs DAS + SQM + Sherlock. Three separate products.

Finspectors

White geometric shape consisting of seven parallelograms on a dark blue background.

Datasnipper

Add-on vs Platform

Tool Tax

Doc-matching is on feature inside a full platform. No separate vendors needed

Always bolted on. Firms still need workpapers, risk tools, QMS, and Excel

Excel vs Audit-Native

Agent Architecture

Agents know scope, plan, and testing. They act within the full audit lifecycle

Agents live inside Excel only. No engagement context outside the spreadsheet

Scope

Risk & Quality

ML engine scores 100% of GL. QM covers all four standards bodies. Both native

No risk engine. No quality management. Enters at execution, stops at execution.

Finspectors

Trullion

Upstream Capability

Starts at materiality, risk, scoping. Downstream agents use those upstream decisions

Enters at fieldwork. Planning, Risk, and materiality are entirely out of scope

Agentic AI Claim

6 agents: Workpaper · Request · Risk · Substantive Test · Review · Reporting.

Trulli is a Q&A chatbot. It does not run audit procedures autonomously.

Audit-Native Design

Built by Chartered Accountants with Big 4 experience. Designed for audit, not adapted.

Core product is lease accounting. Audit added in 2024. Accounting-first architecture.

Fieldguide

Finspectors

Firm Quality Management

No quality management layer. Firm-level governance is out of scope

PCAOB QC 1000, ISQM, SQMS - live, tied to engagement data. Not a module. Native to every audit

Risk Intelligence

AI speeds up procedure execution, Does not score the full GL for risk.

AI/ML scores every GL transaction before fieldwork. Risk is ranked, not sampled.

Audit-Native Depth

Spans SOC, advisory, and financial audit. Broad by design, not audit-native

Built for financial audit by practicing CAs, Audit depth, not advisory breadth.

Inflow

Finspectors

AI Positioning

Inflo's stated position: assistive only. Not to automate conclusions. By design.

Named agents run procedures - Materiality, Evidence Automation, Reviewer, Audit Copilot

Evidence Verification

ADA analytics flag anomalies. Document-level verification remains audito-led

Upload evidence. AI verifies it. You review exceptions only.

Workpaper Generation

Workpapers are managed digitally. Content is still auditot-authored

Workpapers generated from evidence and test outcomes. Agent writes, auditor signs.

CaseWare

Finspectors

Execution Model

AiDA: open -> ask -> verify -> paste.
Auditor still assembles the output

Agent generated workpaper, PBC list and report. Auditor reviews and approves

AI Output Scope

AI produces summaries and narrative only. Core outputs are not AI-generated.

AI produces workpapers, PBC lists, reports, and file-level reviews.

Platform Sprawl

Full coverage needs DAS + SQM + Sherlock. Three separate products.

One platform, one contract, one onborading. Everything included.

Datasnipper

Finspectors

Tool Tax

Always bolted on. Firms still need workpapers, risk tools, QMS, and Excel

Doc-matching is on feature inside a full platform. No separate vendors needed

Agent Architecture

Agents live inside Excel only. No engagement context outside the spreadsheet

Agents know scope, plan, and testing. They act within the full audit lifecycle

Risk & Quality

No risk engine. No quality management. Enters at execution, stops at execution.

ML engine scores 100% of GL. QM covers all four standards bodies. Both native

Testimonials

What users are saying

about us

"A very promising approach to a real industry challenge. Leveraging AI for audit automation and solving data-related hurdles makes this a compelling solution."

‍

Nitin Navish

CEO, Aster Clinics

"Impressive work by the team in tackling long-standing audit pain points. This has the potential to reshape how audits are conducted."

Edwin Chan

Advisor to Board, Computine Group

100+

hours saved per audit

2 weeks

Reduction in average audit timeline

"The evidence automation capability stands out. This tackles a real and pressing problem in the audit space."

‍

Yang Yan

Corporate Finance Lead, Carousell

"Finspectors has completely transformed how our team manages tasks. The platform has made our workflow seamless and boosted overall productivity."

‍

John Mathews

Project Manager

"A very promising approach to a real industry challenge. Leveraging AI for audit automation and solving data-related hurdles makes this a compelling solution."

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