Marketing says $2.1M. Finance says $1.8M. Both are pulling from different sources with different definitions. OWOX creates one governed source of truth — every metric defined once, every team pulling from the same Data Mart, every number traceable to SQL your analyst approved.

Every board meeting starts with "whose numbers are right?" Every budget cycle requires three weeks of data cleanup. Every new report creates another version of "revenue." It’s not a people problem — it’s a definitions problem. And it’s solvable.
Numbers reconcile across every report because the definition lives in one place. That’s it. That’s the fix.
Get started free →Your data team defines each financial metric once. That definition gets published to the library. Every team pulls from it. Done.



Extension puts your financial Data Marts inside Google Sheets. Your FP&A team browses, picks, filters, refreshes.

Insights turn financial data marts into executive narratives delivered on schedule. AI just writes the commentary.


Send this page to your data team. They’ll define revenue, margin, CAC, and LTV as governed Data Marts. Board prep takes minutes, not days.
Your data team defines the metrics. Every team self-serves. AI delivers financial briefs. The reconciliation problem disappears because you eliminated the root cause: multiple definitions.
Each metric gets one SQL definition, one owner, one description. "Revenue" means the same thing everywhere.

Marketing, sales, ops, and finance browse the same library in Sheets. No spreadsheet silos.

Revenue trends, margin shifts, anomalies — delivered before every board meeting. Every number traceable.




When every metric has one definition and one owner, the financial reporting workflow transforms.
Revenue, margin, and CAC numbers are the same everywhere because they come from the same Data Mart. No reconciliation sprint.
Regulators, auditors, your CEO — anyone can trace any number back, the definition, and the analyst who approved it. No black boxes.
When both departments pull "revenue" data from the same source, the $300K gap between their reports disappears.
Finance teams that put one definition behind every metric
The reconciliation problem exists because different teams define the same metric differently — marketing calculates revenue from ad conversions, finance from the ERP, sales from CRM close dates. OWOX solves this by creating one governed Data Mart per metric. "Revenue" gets one SQL definition, one owner, one description of what’s included and excluded. When marketing, finance, and sales pull revenue data in Google Sheets, they all pull from the same Data Mart. Same definition, same SQL, same number. The gap doesn’t need to be reconciled because it doesn’t exist — you eliminated it at the source. If someone needs a different cut (revenue by region, revenue excluding refunds), they use the column picker to add filters or join another Data Mart — but the base definition stays the same.
You can’t trust ChatGPT with financial data — that’s true. An LLM generating SQL on the fly will join the wrong tables, confuse gross and net revenue, and give you a different number every time you ask. One bad number in a board deck can cost you credibility that takes quarters to rebuild. OWOX Insights work differently. Your analyst writes the SQL for each financial metric and publishes it as a Data Mart. The AI Insight runs that pre-approved SQL, computes the exact numbers, and then uses AI to write the narrative commentary around them — "Gross margin improved 2.3pp MoM, driven by reduced COGS in the electronics category." The 2.3pp is deterministic — same SQL, same warehouse, same number every time. AI writes "improved" and "driven by" — the editorial glue. Patented technology.
OWOX connects to the data warehouse where your ERP data lands — BigQuery, Snowflake, Databricks, Redshift, or Athena. Most finance teams already have ERP data replicated to a warehouse via Fivetran, Stitch, or native ERP exports. OWOX doesn’t replace that pipeline — it sits on top of it. Your analyst wraps the ERP tables as Data Marts, defines aliases and join keys, and publishes them. If your ERP data isn’t in a warehouse yet, that’s the first step — but it’s a one-time setup, and tools like Fivetran make it straightforward. Once the data is in the warehouse, OWOX makes it self-serve for your entire finance team.
Every Data Mart has a complete run history — who triggered it, when it ran, whether it succeeded, how long it took, and what SQL executed. Every cell in every report traces back through the Data Mart to the SQL query that produced it. Technical Owner and Business Owner are assigned to every metric. For enterprise customers, OWOX adds monitoring, logging, and role-based access controls — so you can prove to auditors exactly who sees what data and how every number was computed. The audit trail goes from board slide → Sheets cell → Data Mart → SQL query → warehouse table. No black boxes anywhere in the chain.
A semantic layer project with dbt + Looker is the gold standard for enterprise data governance — and it typically takes 6–12 months, requires dedicated analytics engineering headcount, and costs six figures in tooling. OWOX compresses this dramatically. Your analyst wraps existing dbt views as Data Marts in two clicks. OWOX auto-generates aliases, descriptions, join keys, and ownership. Business users self-serve in Sheets via the Google Sheets Extension — no Looker training, no explore-mode complexity. You get 80% of the semantic layer value in 5% of the time. And the two approaches aren’t mutually exclusive: if you already have dbt models, OWOX is the last-mile self-service layer that makes them accessible without Looker licenses.
Cloud Starter is $30/month — that includes Data Mart management, the Google Sheets Extension, and Looker Studio destination. For a finance team that needs AI-narrated financial briefs, multi-destination delivery, and SLA, Team plans start at $875/month. Enterprise is custom pricing with SSO, RBAC, monitoring, and audit logging. For context: one reconciliation sprint before a board meeting typically burns 40+ analyst hours at $60–80/hour — that’s $2,400–$3,200 in analyst time, four times a year. OWOX eliminates that entirely by solving the root cause.
Send this to your data team. They’ll define your financial metrics as governed Data Marts. Every team pulls the same number. Board prep takes minutes.
See how your financial metrics flow from warehouse to governed Data Marts to board-ready briefs — with your actual chart of accounts in mind.