10,000+ Transactions.
Zero Manual Reconciliation.
CarbonZero was reconciling 10,000+ carbon offset transactions every month with a single analyst. Real-time reporting was impossible and the entire process depended on one person. Quixas replaced the workflow with a LangGraph + Python pipeline that runs reconciliation at transaction time. Live dashboards, automated audit trails, and volume that scales without headcount.
Industry
Carbon Markets & Climate Finance
Volume
10,000+ transactions per month
Delivered
Real-time reconciliation pipeline
Monthly Reconciliation Load
0 hrs
Manual reconciliation work eliminated
The analyst who ran the monthly cycle now works on strategy and client relationships instead of registry matching.
10K+
Tx processed monthly
~0%
Entry error rate
24/7
Live reporting
0
Transactions / month
Processed automatically, real time
0 hrs
Manual reconciliation
Eliminated entirely
~0%
Data-entry error rate
Validated before write
24/7
Live GHG reporting
No more monthly snapshots
A Single Analyst Holding
The Entire Reporting Pipeline.
One analyst responsible for 10,000+ monthly transactions
Every transaction had to be matched against project registry data, validated against GHG methodology, categorised, and entered into the reporting system. The process was accurate but its capacity was capped by one person.
Scale dependency — the workload grew linearly with volume
A month with 12,000 transactions took meaningfully longer than a month with 8,000. As the business grew, the reconciliation timeline grew with it, with no room to catch up.
Real-time reporting was impossible
Clients and partners needed current offset data, but the data only existed in the reporting system after month-end reconciliation. Dashboards were always weeks behind reality.
Single point of failure and compounding error risk
If the analyst was unavailable, reconciliation stopped. Manual data entry at scale introduced errors that cascaded through client dashboards and audit records, each one requiring downstream correction.
A Real-Time
Reconciliation Pipeline.
Quixas built an automated reconciliation pipeline using LangGraph and Python that processes every transaction the moment it enters the platform. No batch jobs, no queuing, no month-end scramble.
Ingestion
Event-driven capture
Registry Match
Multi-registry API
Validation
GHG methodology check
Categorisation
Type / project / year
Live Reporting
Dashboards + audit
From Month-End Scramble to Real-Time Pipeline.
Diagnose & Map
Walked the analyst through every step of the monthly cycle, mapped the registry sources, edge cases, and methodology variants, and defined the validation rules.
Pipeline Build
Built the LangGraph orchestration, transaction ingestion, registry connectors, and validation layer in Python. Modelled the categorisation logic against historical data.
Reporting & Audit Layer
Wired the reporting database and live dashboards, implemented continuous audit-trail generation, and ran the pipeline in parallel against a back-catalogue of past transactions.
Cutover & Handoff
Switched the live transaction flow onto the automated pipeline, handed the analyst a human-review queue for flagged discrepancies, and documented runbooks for ongoing ownership.
Real-Time GHG Tracking
At Any Transaction Volume.
10K+
Transactions processed monthly
Volume growth no longer creates a linear increase in operational burden. The pipeline processes 10,000 or 50,000 transactions with the same overhead.
~0%
Manual data-entry errors
Automated validation and categorisation eliminated the class of errors introduced by manual data entry. Discrepancies are caught before they touch the reporting system.
24/7
Live reporting layer
Reconciliation happens at transaction time. Client dashboards reflect current data continuously rather than delivering monthly snapshots that are already weeks old.
100%
Continuous audit readiness
The audit trail is generated automatically with every transaction rather than assembled retrospectively at the end of each reporting period.
We went from reconciling everything by hand at month-end to having a pipeline that catches issues before they reach the reporting layer. Our analyst now works on the questions that actually need her judgment, not on matching transactions against registries one at a time.
Head of Operations
CarbonZero
Is Your Reconciliation Scaling
With Headcount Instead of Volume?
We have built reconciliation and reporting pipelines that handle 10,000+ transactions per month with no manual touch. In 30 minutes we map your current workflow, identify the automation architecture, and estimate the time saved before any build begins.