Capability is converging
Reasoning, code generation and long-context retrieval get cheaper every quarter.
Your knowledge is the edge a competitor can't license.
Connecting the data was the easy part. What your company knows is the real asset, and almost none of it is written down.
--- concept: arr owner: finance verified_by: revops-lead valid_from: 2026-01-01 links: [contract, invoice, segment] --- # ARR Recognized revenue from active contracts. Amendments count once they are billed.
Every company now has the same models at roughly the same price. The advantage moves to what you feed them.
Reasoning, code generation and long-context retrieval get cheaper every quarter.
Your knowledge is the edge a competitor can't license.
Years of decisions about discounts, exceptions and metrics are tuned weights, stored in people, Slack threads and a file called final_v3_USE_THIS.
When someone leaves, the weights leave too.
A new hire absorbs the unwritten rules over six months. An agent gets whatever is in front of it right now.
Written meaning makes agent answers right.
The organizations that win the next decade will be the ones whose knowledge is in a form a model can use.
Lakehouses, connectors and semantic layers put all the data in one place. We build this, and it is necessary.
Two agents can still read the same clean warehouse and return two different numbers. Neither is broken. The organization never wrote down which number it means when it says ARR.
Pipelines move the data. Meaning needs a layer of its own.
Both agents are correct. ARR was never defined.
A shared definition of ARR fixes this.
The people who hold the meaning work in finance, ops and platform teams. So the ontology lives as markdown in version control: reviewed in a pull request, readable by a person, parseable by an agent.
In June 2026 Google published the Open Knowledge Format on the same idea. We implement it, and our runtime enforces access, explains decisions and remembers the past.
Google shipped the format. The runtime is the part we built.
What was true and what we knew are separate questions. Contracts get amended after the fact and accounts get reclassified backwards.
DataGOL stores both by default, so any closed quarter rebuilds exactly as it was believed and every number holds up in front of an auditor.
Markdown in version control, readable without tooling, reviewable in a pull request.
Your ontology walks out as a folder of files any system can read.
Pipeline shape follows your cost ceiling, latency needs and where your data lives.
Bitemporal by default, so a closed quarter rebuilds exactly as it was believed.
Every correction writes back with provenance attached, so the system improves with use.
Access policy, lineage and audit are enforced at query time.
We send engineers. The ontology ships with a name attached to it.
Every question someone asks makes the next answer better.
All ten pages, including the full argument behind each commitment. Flip through it here or take the PDF with you.
Their understanding of their own business is written down, carries its own history, and gets better every time someone asks it a question. That's infrastructure. We're building it.