Account reconciliation software that closes your books 80% faster

Bluecopa matches 97 to 99% of transactions across every source, resolves exceptions on auto-pilot, and posts journals that are audit-ready by design.

A 15 minute walkthrough on your own reconciliation data. No commitment.

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80%
Faster month-end close
5M+
Records per hour
97-99%
Matching accuracy
75%
Lower exception rate
Trusted by the world’s leading finance teams
Recon Control Tower · Samyx Recon
Live
Matching accuracy
98.2%
within 97 to 99% band
Exception rate
4%
down from 15 to 20%
Days to close
3.5d
down from 8 to 12 days
Reconcile invoices and remittances in Bluecopa
Illustrative product view. Accuracy and close ranges are Bluecopa published benchmarks; row-level records are sample data.

The intelligence layer behind every reconciliation

SamyxAI is Bluecopa’s unified intelligence layer for enterprise finance. Rather than a general purpose LLM bolted onto a rules engine, it runs purpose built models for the four jobs reconciliation actually needs.

Samyx Extract turns PDF, DOCX, XLS, CSV and EDI documents into validated records. Samyx Recon matches transactions with multi-field fuzzy logic. Samyx Narrate explains the variances. Samyx Build posts to your ERP through approval gates.

That is why it holds 97 to 99% matching accuracy at more than 5,000,000 records per hour, where a generic LLM manages 10,000 to 50,000.

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80%
Less reconciliation time
8 to 10 days
1 to 2 days
80%
Fewer staff hours
1,500+ per month
75 to 150 per month
75%
Lower exception rate
15 to 20%
3 to 5%
80%
Lower cost per transaction
$0.15 to $0.25
$0.01 to $0.03

How does automated account reconciliation software work?

Automated reconciliation replaces the download, VLOOKUP and chase cycle with a continuous pipeline: ingest, normalise, match, resolve, post. Bluecopa runs all five with a Samyx agent behind each stage, and every stage leaves an evidence artifact.

Auto-advancing walkthrough
❚❚ Pause
1Ingest and extract from every source

Samyx Extract converts documents in PDF, DOCX, XLS, CSV and EDI formats into validated records using vision and language models with schema aware parsing. Structured feeds arrive through pre-built integrations, so nobody downloads a statement by hand.

2Normalise into validated records

Currencies, date formats, reference IDs and narration strings are standardised into one canonical transaction model. Matching downstream is only ever as good as the data it runs on, which is why account classification runs at 95 to 98% accuracy before a single match is attempted.

3Match transactions with Samyx Recon

Samyx Recon automates transaction matching with multi-field fuzzy matching, confidence thresholds, duplicate detection and real-time dashboards, hitting 97 to 99% transaction matching accuracy at more than 5,000,000 records per hour.

4Resolve exceptions on auto-pilot

Unmatched items are identified at 93 to 96% accuracy and routed with a suggested resolution from Samyx Narrate, which adds variance analysis, trend insights, KPI summaries and anomaly detection. Policy gates decide what auto-clears and what needs a human sign-off, taking the exception rate from 15 to 20% down to 3 to 5%.

5Post to the ERP and close

Samyx Build runs policy gated agents that handle AP and AR workflows from capture through ERP posting, with approval gates and evidence artifacts attached. Month-end close compresses from 8 to 12 days down to 3 to 5.

Samyx Extract, ingestion pipeline
Live
Data ingestion on auto-pilot
Samyx Extract handles PDF, DOCX, XLS, CSV and EDI with schema aware parsing. Row values are sample data.
Normalise into validated records
Live
Records normalised
627,525
validated
Classification
96.4%
95 to 98% band
Conflicts fixed
1,842
auto-resolved
Consolidate and enrich financial data
Illustrative field mapping. Sample data.
Match transactions with Samyx Recon
Live
Auto-matched
616,127
98.2%
Suggested
9,780
1.6%
Unmatched
1,618
0.2%
Continuous transaction matching
Confidence thresholds and duplicate detection are Samyx Recon capabilities. Row values are sample data.
Resolve exceptions on auto-pilot
Live
Instant exception detection and resolution
Exception identification runs at 93 to 96% accuracy with AI suggested resolutions from Samyx Narrate. Row values are sample data.
Samyx Build, ERP posting
Live
Journals posted
1,284
to SAP
Gates cleared
1,238
evidence attached
Close status
3.5d
from 8 to 12 days
Automated journal entry calculation and posting
Samyx Build posts through approval gates with evidence artifacts. Row values are sample data.

Account reconciliation software use cases

One reconciliation engine for every reconciliation type. Each use case runs on the same Samyx Recon core, so controls and evidence stay consistent.

Close and Reconciliation

✓Financial Reconciliation
✓Financial Close

Transaction Matching

✓Transaction Matching
✓Invoice Reconciliation
✓Balance Sheet Reconciliation
✓Multi-Entity Reconciliation

Data and Ingestion

✓Enterprise Reconciliation

Reporting and Analysis

✓Financial Reporting
✓Variance Analysis

Across the Finance Stack

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15 minutes on your own reconciliation data.

Reconcile any financial data, across the stack you already run

Samyx Extract converts documents into validated records and pre-built connectors pull the rest, so the answer to “will it handle our data” includes the messy parts. Your ERP stays exactly where it is.

Data we reconcile

Formats we ingest
PDF
DOCX
XLS
CSV
EDI
Excel
Sheets
What we reconcile against
General ledger
AR sub-ledger
AP sub-ledger
Revenue
Intercompany
Balance sheet
Cash and bank

Systems we connect to

ERP and accounting, ingest and post
SAP
NetSuite
Sage Intacct
Xero
Zoho Books
QuickBooks
Payments, orders, warehouses, CRM, BI and HRM
Stripe
PayPal
Shopify
Chargebee
BigQuery
Databricks
Redshift
Salesforce
Tableau
Workday
ADP
Power BI

Bluecopa vs other enterprise reconciliation platforms

The things enterprise finance teams tell us break their reconciliation, and how each option handles them.

The problem you are trying to solve
Other enterprise platformsLegacy suites and close tools
BluecopaAI-native finance data layer
Data that lives outside your ERP
Gateways, order systems, warehouses, spreadsheets
~Strong inside the ERP, patchy outside it
✓Every source normalised into one model before matching
PDF and EDI becoming matched records
Statements and invoices that are not tables
✕Usually needs a separate document capture product
✓Samyx Extract parses PDF, DOCX, XLS, CSV and EDI natively
Net of fee and one to many settlements
Where the amounts never match exactly
~Rule based and largely one to one, fuzzy often costs extra
✓Multi-field fuzzy matching at 97 to 99% accuracy, included
Exceptions that explain themselves
Not just a red flag on a queue
~Flagged and queued, root cause left to the analyst
✓Root cause at 93 to 96% with an owner and a suggested fix
Throughput at month-end peak
When volume triples in three days
~Batch windows and licence tiers govern the ceiling
✓5,000,000+ records per hour on purpose built models
Going live this quarter
Not in eighteen months
~Deep ERP integration means long implementation programmes
✓Sits above your ERP, so no migration and no core system risk
Audit evidence without the scramble
SOX, statutory and internal review
~Trails exist, evidence often reassembled at audit time
✓Evidence artifact on every match, 80% less audit-prep time
One platform beyond reconciliation
Close, O2C, P2P and reporting
~Broad suites, or narrow close orchestration only
✓Continuous close, order to cash, procure to pay and reporting

Four differences that show up in your first close cycle

Not a feature list. These are the four architectural choices that change what your team experiences at month end.

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01

Purpose built models, not a general purpose LLM

Samyx models are trained for matching, classification and exception identification. That is why throughput and accuracy hold together instead of trading off against each other.

5M+records per hour against 10,000 to 50,000
02

Data depth before matching, not after

Samyx Extract turns PDF, DOCX, XLS, CSV and EDI into validated records first. Most platforms match first and clean up later, which is why their accuracy collapses on messy sources.

95 to 98%account classification accuracy
03

Controls are the default, not a configuration project

Human-in-the-loop review and policy gated approvals ship switched on, with an evidence artifact attached at the match level. ISO 27001 certified and SOC 2 Type II attested.

80%less audit-prep time
04

One platform above your ERP, not inside it

Reconciliation, continuous close, order to cash, procure to pay and management reporting run on the same finance data layer. Your ERP stays where it is and receives approved journals only.

80%faster month-end close

Enterprise finance teams already reconciling on Bluecopa

Named customers, their published numbers, and what changed after reconciliation automation.

“Bluecopa reconciliation automation has reduced 95% of manual efforts. With real-time cash flow visibility, we’ve optimized cash management for accelerated business growth.”

Chief Financial Officer, Yatra.com
95%
Reduction in manual reconciliation effort at Yatra.com
Diversey Holdings
80%
Improvement in visibility across finance operations
Enterprise financial services
60%
Reduction in reconciliation errors, close cut from days to a few hours
HRMS SaaS
45%
Improvement in operational efficiency across finance workflows
HackerEarth
VP Finance
Reconciliation accuracy improvements documented with the finance lead

Account reconciliation software, frequently asked questions

What is automated account reconciliation software?

Automated account reconciliation software ingests records from every relevant source, converts documents into validated records, matches transactions using AI, routes unmatched items for resolution, and posts approved journal entries back to your ERP with evidence attached. It replaces the manual download and VLOOKUP cycle with a continuous, controlled process.

How does an account reconciliation tool work?

In five stages: extraction and ingestion, normalisation into validated records, transaction matching, exception resolution, and journal posting through approval gates. Bluecopa runs all five with a dedicated Samyx agent behind each. See how it works for the walkthrough of each stage.

What are the benefits of automated account reconciliation?

Bluecopa’s published SamyxAI benchmarks show an 80% reduction in reconciliation time from 8 to 10 days down to 1 to 2, an 80% reduction in staff hours from 1,500+ a month down to 75 to 150, a 75% lower exception rate from 15 to 20% down to 3 to 5%, an 80% lower cost per transaction, and a month-end close 80% faster at 3 to 5 days. Yatra.com removed 95% of manual reconciliation effort.

How accurate is AI transaction matching?

Samyx models run transaction matching at 97 to 99% accuracy, account classification at 95 to 98%, and exception identification at 93 to 96%, using multi-field fuzzy matching, confidence thresholds and duplicate detection.

How is Bluecopa different from other enterprise reconciliation platforms?

Bluecopa normalises every source into validated records before matching, which is why accuracy holds on messy multi-source data, and it runs on purpose built models rather than a general purpose LLM. It also sits above your ERP rather than replacing it, so approved journals post back without a migration project. See the full comparison.

Future-proof your finance operations, today

Automate complex finance processes and systems. Accelerate decisions with Bluecopa's Al-powered, real-time insights.
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