Finance Automation Platform
Compress month-end close by 38%, with audit trails your auditor will thank you for.
The problem
Your finance team works 60-hour weeks for the last fortnight of every month. The close runs 14 days. Three of those days are intercompany reconciliation across four ERPs. Four are manual journal entries based on accruals templates that live in a spreadsheet your senior accountant maintains. Two are management reporting cycles where the same number gets calculated three times in three different decks.
McKinsey's 2024 Finance Function 2025 research finds that mid-market finance teams using generative AI for reconciliation, accrual, and reporting workflows compress month-end close by a median 38%, while reducing audit-adjustment volume by 24%.[^1] The opportunity is large, the technology is mature, and most CFOs have not yet built the operating model to capture it.
Our approach
Source systems: SAP / Oracle / NetSuite / Workday / Yonyou / Kingdee
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Data ingest layer (Airbyte connectors → Snowflake / BigQuery)
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Reconciliation engine
- rule-based matching (deterministic)
- LLM matching (Claude Sonnet 4.6) for fuzzy cases
- intercompany match scoring
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Accrual + journal proposal engine
- LLM-drafted entries with source citation
- human approval gate (Laravel + Filament)
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Management reporting layer
- narrative generation (Claude Sonnet 4.6)
- chart and table assembly
- export to Excel / Google Sheets / PowerPoint
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Audit log: every input, every model decision, every approver, every output
Who it is for
- The Group CFO of a 700-person manufacturing group in Taiwan running consolidation across four legal entities and three ERPs.
- The Finance Director of a Hong Kong holding company with 14-day close pressure from listed-parent reporting deadlines.
- The Head of Finance at a 350-person SaaS company in Singapore trying to scale the finance team without a 1:1 headcount-to-revenue ratio.
Tech stack
- Data ingest: Airbyte (open-source connectors for ERPs and SaaS), custom Laravel connectors for proprietary systems
- Warehouse: Snowflake (default), Google BigQuery, or Databricks depending on existing footprint
- LLMs: Claude Sonnet 4.6 for reconciliation reasoning and narrative generation, Claude Haiku 4 for high-volume classification
- Approval workflow: Laravel 12 + Filament 3 admin UI with role-based approvers
- Audit log: Append-only event store (AWS QLDB or equivalent), exportable for auditors
- Reporting export: PhpSpreadsheet for Excel, Google Sheets API, PptxGenJS for PowerPoint
Integration list
SAP ECC and S/4HANA, Oracle EBS and Fusion, NetSuite, Workday Financials, Microsoft Dynamics 365 Finance, Sage Intacct, Xero, QuickBooks, Yonyou, Kingdee, OBIC7, BlackLine (sidecar mode), FloQast, Snowflake, BigQuery, Power BI, Tableau, Excel, Google Sheets.
Deployment timeline
| Week | Activity |
|---|---|
| Week 1-2 | Close-process audit; identify top 3 time sinks; success metrics agreed |
| Week 3-4 | Data ingest pipelines built; reconciliation rules defined |
| Week 5-6 | LLM reconciliation tested against 6 months of historical data |
| Week 7-8 | Approval workflow live in staging; CFO walkthrough |
| Week 9-10 | First close run in shadow mode (parallel to manual close) |
| Week 11-12 | Cutover; second close runs live with reduced manual fallback |
Mini-ROI
A 700-person manufacturing group in Taiwan compressed month-end close from 13.5 days to 6.5 days in the first three closes post-cutover. Audit-adjustment volume dropped 31% in the year-end audit. The CFO redirected two FTEs into FP&A capacity rather than headcount reduction. Total annualised value: US$420,000.
McKinsey benchmarks the value at US$220,000-US$580,000 annually per 100 finance staff for fully-deployed reconciliation, accrual, and reporting automation in mid-market enterprises.[^1] IDC adds that audit costs decline 8-15% in year two as audit trails improve.[^2]
Pricing tiers
| Tier | Setup (one-time) | Monthly run cost | Best for |
|---|---|---|---|
| Starter | US$32,000 - US$58,000 | From US$2,400/mo | Single ERP, 1-2 close workflows automated, single legal entity. |
| Scale | US$75,000 - US$160,000 | From US$5,800/mo | Multi-ERP, 4-6 close workflows, intercompany consolidation, management reporting. |
| Strategic | US$180,000 - US$340,000 | From US$11,000/mo | Group-level consolidation, 4+ legal entities, regulatory reporting, dedicated audit support. |
All tiers include the year-end audit support sprint and an external auditor walkthrough.
Frequently asked questions
Will the auditors accept AI-assisted journal entries? Yes, when the audit trail is complete. Every model-proposed entry logs the source data, the prompt, the model output, and the human approver. We have walked Big Four auditors through three deployments — none have raised methodology objections. Your auditor sees a more thorough trail, not less.
Can the model post journals automatically? Only within strict guardrails. Standard recurring accruals below a configured value can post automatically with batch approval. Material entries always route to a named human approver. The threshold is set by you and changeable in the admin UI.
What about regulatory reporting (J-SOX, MAS, HKMA)? We deploy with regulatory-reporting templates pre-configured for J-SOX (Japan), MAS-TRM (Singapore), and HKMA (Hong Kong) where relevant. New regulatory templates are built on a fixed-fee basis (typical: US$12,000-US$24,000 per regime).
How does intercompany reconciliation work? The engine matches transactions across entities using deterministic rules first (currency, amount, counterparty, date) then LLM matching for fuzzy cases (description variations, currency conversion timing differences). Match confidence is scored. Unmatched items route to a human queue.
Can we keep our existing close tool (BlackLine, FloQast)? Yes. We deploy as a sidecar that augments your existing close tool rather than replacing it. The Platform writes match results, journal proposals, and reconciliation reports into BlackLine or FloQast via API.
Where does the data live? In your cloud account, your chosen region. Default deployments use Snowflake in the AWS region matching your data residency requirement (Tokyo, Singapore, Sydney, or Mumbai). For Mainland China, we deploy on Alibaba Cloud with PIPL-compliant logging.
What is the impact on the finance team's role? Reduced manual entry, increased review and analysis. Across the last 8 deployments, finance teams reported a 41% reduction in time spent on data preparation and a 28% increase in time spent on FP&A and decision support. Headcount stayed flat in 6 of 8 cases.
How do we handle the first close after cutover? Parallel-run the first close (shadow mode) and the first live close with manual fallback ready. We sit beside the controller during both. We have not had a failed first-close cutover in the last 14 deployments — but we plan as though we might.
Where this is most often deployed
Industries where AIMenta frequently scopes this kind of solution.
Beyond this solution
Browse our other productized solutions, plus the verticals and Asian markets where they ship.
Other solutions
By industry
By Asian market
Frequently asked questions
Which finance processes does the platform automate in phase one?
The standard phase-one scope covers: invoice ingestion and three-way matching (PO, goods receipt, invoice), AP payment authorisation routing, month-end journal entry generation from sub-ledger feeds, and FX exposure reporting. Payroll, treasury, and management reporting typically land in phase two once the core AP/GL integration is stable.
How does the platform handle multi-currency and multi-entity operations?
Multi-currency is native: the platform subscribes to live FX rates (ECB, HKMA, MAS feeds) and applies revaluation at configurable frequencies. Multi-entity consolidation uses a parent-subsidiary ledger model that mirrors your group structure, with intercompany elimination rules configured during implementation.
What audit trail and controls satisfy Big Four / external auditors?
Every AI-generated entry or match is stored with a full provenance record: model version, confidence score, input documents, timestamp, and the human reviewer who approved it. The audit log is immutable (append-only table with cryptographic hash chaining) and exportable in Excel or CSV format for auditor review.
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