// How it works

The timber data platform is a layer, not a migration.

Your ERPs, databases and spreadsheets stay exactly where they are. Quarri governs them into one layer and makes them usable by any leading model, without a migration project or a five-year platform bet.

// Keep

  • Your ERPs, mill systems and databases
  • The spreadsheets your team trusts
  • How your people already work

// Add

  • A governed layer over all of it
  • Safe read + write into your systems
  • AI, dashboards and automation on top
// Where Quarri sits

Under the model. Over your data.

General-purpose models sit on top and do the reasoning. Quarri is the layer beneath them that holds your data, your definitions and your workflows, and it reads and writes back into the systems you already run.

// Horizontal AI

General-purpose models reasoning

Open source Your own agents

Quarri an MCP plugin

Product layer what your team uses
Document extractionReconciliationForecastingSmart SchedulerMargin intelligenceBuild
Infrastructure layer deterministic execution
100+ agent toolsVersioned workflowsReusable across teams
Context layer
Semantic modelCompany glossaryMemory of work
Data layer
WarehouseAgentic modellingRole-based data accessRead + write
Connectors & ingestion
Daily syncAPIs & databasesScanned documentsExternal feeds
// Your sources
Paper & handwrittenLegacy ERPMill systemsSpreadsheetsDatabasesScanned PDFsExternal data

Model your data once, then any workflow builds on top. One source of truth, flexible, fast to build and cheap to run.

// The process

Three steps from messy reality to working intelligence.

Every Quarri deployment starts the same way. We don't replace your stack, we make it usable by AI.

01

Connect.

Legacy ERPs, databases, spreadsheets, scanned PDFs and paper documents. Around half a day per source, absorbed in the SaaS fee.

02

Clean.

Automatically cleaned, deduplicated and structured into one queryable layer, with the reconciliation logic encoded as rules.

03

Contextualise.

Your business rules, metrics and definitions, species, grades, units, cost centres, embedded so AI answers in your language.

// Built once, used everywhere

Every workflow you build is reusable, shareable and yours to edit.

A reconciliation built for the finance team's month end does not stay with the finance team. It is versioned, documented and available to operations the next morning, and anyone with access can open it, read exactly what it does and change it. That is the part that compounds.

Shared across teams

Built once in finance, reused in operations, no rebuild and no second version drifting out of sync.

Versioned, not fragile

Every change is tracked and every edit runs against a verification harness before it lands. If something breaks, roll it back.

Open, not a black box

Your people can read the logic, see which rule produced a number and change it themselves. No ticket, no vendor.

Outputs persist

Workflows saved, dashboards live, data captured and written back into your ERP rather than exported and forgotten.

// What we actually do

The part that isn't software.

Software that needs a data team is not much use to an operator who does not have one. So we do that work. Connecting the systems, modelling the data, encoding the rules your business already runs on and automating the processes that carry risk. It is included, it is where most of the early value comes from, and it is the part nobody puts on a website.

01

Fix the foundation

Connect the systems you already run and build a clean model on top of them. The rules your team carries in its head get written down: rate tables, department mappings, the exceptions everybody knows and nobody documented.

02

Automate what carries risk

Replace the manual processes where an error costs money. Reconciliations, accruals, extraction from paper. Each one gets validation checks so a mistake is caught by the process rather than by somebody noticing.

03

Hand it over

Your power users learn to build, not just to read. Standalone workbooks get retired as people query the data directly, and the team that runs the operation stops queuing behind whoever owns the spreadsheet.

04

Keep building

Forecasting, new sources, cross-business views. Each workflow built is reusable, so the second and third are faster than the first, and what we learn on one process carries into the next.

Week 1

Kick-off, priorities agreed, first systems connected. Around half a day per legacy source, absorbed in the fee.

Week 2

First workstream live in production, not in a sandbox. This is what "live in two weeks" means.

Month 2 onward

Development days each month for new automations, a monthly call to set priorities, and maintenance of everything already running.

Your contribution to data organisation, cleaning and catching improvements in process flow is two thirds of the value.

Customer, forestry operation
// Why deterministic

Encoded logic on the data. AI on the reasoning.

Quarri is a deterministic layer beneath probabilistic AI. The matching, converting and reconciling runs as encoded workflows, replayable, auditable and with no model call per document, so the numbers in front of your board are never guessed. Every figure below traces to a live deployment.

0
LLM calls per document on extraction, fully replayable and auditable
~1 sec
To re-solve a full order book, within 1% to 1.6% of a brute-force optimum
<30 sec
Full reconciliation runtime, replacing a 4-minute previous build
125
ERP tables synced daily at a single mill deployment

See it on your own data.

Live in two weeks, on the systems you already run.