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Unify informationOnnu BioSource · dMRV

Using machine data to ensure compliance at an industrial plant

Making carbon audits and carbon reporting automated, with little-to-no time needed to produce reports.

Return on investment
1hour per day taking readings savedReporting ready outputs logged automatically.
4hour per week compiling reports savedOutputs match required format.
£10kper year saved on off the shelf dMRV systemsAvailable alternatives are expensive.

Cashflow positve

Reliable compliant data means more regular carbon credit issuance, bringing cash into the business more frequently with less delay.
Background

Industrial pyrolysis plants, streaming live telemetry

Our client is a biochar project developer that operates industrial pyrolysis plants, converting biomass feedstock; oil palm trunk, empty fruit bunches, and others, into biochar. Each plant streams live PLC data across roughly 155 sensor registers: temperatures, motor currents and speeds, gas and pressure, flow, and alarms.

The challenge

No structured way to prove a run met MRV requirements

Machine telemetry and business/compliance data lived apart, with no structured way to prove a production run met MRV (Monitoring, Reporting, Verification) requirements.

01

No single connected record

Nothing connected what feedstock went into a run, how the reactor actually performed, and whether that run qualified for compliance or carbon claims.

02

QA that wasn't logged

Operator QA during a run was ad hoc rather than logged.

03

Alarms and tags nobody could read

Raw PLC alarm codes and sensor tags weren't decoded into anything a compliance report or operator could read directly.

04

Business data, siloed from the run

Feedstock, lab result, customer, and site data lived separately from the run data they related to.

Mainspring solution

A connected platform, built around MRV

[One or two lines introducing the tool — to be completed]

  • Live telemetry, tied to the businessLive PLC data is ingested through Node-RED into a REST API, with sensor tags mapped to human-readable names, units and scale factors — then tied to each run's feedstock, customer, site and lab data.
  • A structured compliance record, per runAn MRV module generates a structured compliance record for every run: residence time, main-phase windowing, machine configuration and one-minute telemetry — evidence for a claim without manual reconstruction.
  • QA and alarms, made auditableAn Auditor module logs hourly operator checks against each run, and raw PLC alarm codes are decoded into human-readable, per-site alarm names — turning QA into an auditable record.
The outcome

One connected system, not reassembled by hand

Machine telemetry, compliance data, and business/feedstock data now sit in one connected system:

A run's compliance case is generated automatically, rather than reassembled by hand from raw logs.
Hourly QA is now systematic and auditable, rather than dependent on individual operator diligence.
Data quality is actively verified against real production data — the team has caught and corrected reporting discrepancies, such as an energy metric, before they were reported onward.
The platform has grown from an initial feedstock-tracking tool into a full operations system, reflecting sustained ongoing investment rather than a single build-and-done project.
Onnu BioSource MRV compliance record screen

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Tejas Rajput · Solution Engineer