FINANCIAL RECONCILIATION PLATFORM | MALAYSIA

Reconciliation,
settled.

Darkwire ingests your ledger and bank data, resolves the entitites, runs an exact-to-semantic match cascade, and surfaces only the breaks that actually need a human. Close the month in hours, not weeks.

02 · HOW IT WORKS

One pipeline, five stops
between raw data
and a settled book.

Every transaction takes the same path. The interesting work happens in stages three and four — but stages one and two are why the matchers actually work.

01 · INGEST

Sources land

CSV, ISO-20022, SFTP, BAI2, Plaid, or direct DB pulls — Darkwire normalizes every shape into a canonical row.

02 · NORMALIZE

Cleaned & canonical

Currencies, dates, signs, and FX adjustments are aligned to a single chart of accounts and reporting period.

03 · RESOLVE

Counterparty entities

"STRIPE *PAYOUT," "Stripe, Inc.," and "stripe treasury llc" collapse to one resolved entity with provenance.

04 · MATCH

Cascade & solver

Exact → fuzzy → semantic, then a many-to-many optimizer for splits, partials, and netted offsets.

05 · DETECT

Fraud & anomaly

Runs in parallel to matching. Velocity, novelty, and pattern-break signals flag what to escalate.

THE MATCH CASCADE

99% of decisions are deterministic. The AI advises on the rest.

Each transaction enters the cheapest, most defensible matcher first. Anything that can be settled by arithmetic — is. The semantic layer only runs on what's left, and even then it produces a recommendation, not a decision.

01Exact match0.0%
02Fuzzy & tolerance0.0%
03Many-to-many solver0.0%
04Semantic (AI advisor)0.0%
05Human review queue0.0%

03 · CAPABILITIES

The boring features finance teams keep asking for.

Built for month-end close, audit defensibility, and the two-page memo your controller will send to the audit committee.

Entity resolution that hold up in audit

Every resolved counterparty carriers a full lineage - which raw strings collapsed, by which rule, and who confirmed the merge.

Explore More

Many-to-many splits & nets

One ledger entry covering four bank deposits. One deposit netting twelve refunds. Darkwire solves the combinatorics directly.

Explore More

Six-signal confidence index

Every match exposes its component score - amount, date, counterpay, memo, currency, history - so reviewvers know why.

Explore More

Fraud & anomaly in paraller

A separate signal layer runs alongside matching: velocity breaks, novel counterparties, structuring, and timing oddities surface to their own queue.

Explore More

Drop-in connectors

NetSuite, Sage Intacct, QuickBooks, Stripe, Mercury, Brex, JPM Access, ISO 20022 feeds - without the data-team rewrite.

Explore More

Close 6x faster, audited

Teams report month-end close compressed from 9 days to 36 hours, with every decision trail exportable to PBC.

Explore More

04 · THE ADVISOR PATTERN

The AI advises. A human decides. Every single time.

Darkwire writes recommendations the way a careful junior would — with the reasoning attached, in language a controller would write to her board. Auto-match runs only where deterministic rules already passed. Everywhere else, you sign off.

See an advisor recommendation in the demo →
ADVISORQ3-CLOSE · ROW 1,148
CONF · 87.2
RECOMMENDMatch JE-40221 against Mercury credit on 14 Oct — amounts agree within 0.0% tolerance, memo similarity 0.92, counterparty entity resolved (Stripe, Inc.).
CAVEATMemo string “acct_1QAk · po” has not been observed on this account before; new merchant ID first-seen 11 days ago. Worth a sanity check.
0%
DETERMINISTIC DECISIONS
0h
AVG. MONTH-END CLOSE
0.0M
TXNS / DAY, PER TENANT
0%
AUTO-ACCEPTED BY AI ALONE

GET A DEMO

Close the month, not the week.

30-minute walkthrough with your controller in the room. We bring two months of your own data to the cell.