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Commercial operations infrastructure

Turn data into a governed, commercial asset — without giving up control of it.

GateHouse is the operating layer that lets data owners realise the true value of their data in the cloud: provisioning access through a governed access framework that keeps privacy, consent, and control intact at every step.

Metadata-only control plane · 0 rows ever exported
Data stays in place
No bulk export. Access is brokered, not copied.
Internal and external access requests are governed
Policy, consent, and purpose are enforced before a query runs.
Value is metered and paid
Usage is priced, tracked, and settled automatically.
Cloud-native by design
Deploys inside your existing cloud estate, not alongside it.
Runs in the cloud you already use
  • Snowflake
  • Databricks
  • Google Cloud
  • AWS
The problem we solve

Valuable data sits idle because access and monetisation are unsolved commercial problems, not just technical ones.

Most data owners have the pipes. What's missing is the commercial operations layer: the governance, pricing, and access control needed to let others use the data safely — and to get paid for it.

Without GateHouse

Data is either locked down entirely, or shared through ad hoc exports, one-off contracts, and manual approvals. There's no consistent way to enforce privacy rules, no visibility into who's using what, and no mechanism to price or capture value.

With GateHouse

A governed access framework sits in front of your data: every request is checked against policy and consent, every query is scoped to what's permitted, and every unit of value exchanged is metered, priced, and settled — automatically, and with a full audit trail.

What GateHouse provides

Commercial operations infrastructure, purpose-built for data.

Governed access framework

Policy-driven controls determine who can access what, under what conditions, and for what purpose — enforced automatically, not by manual review.

Privacy by design

Consent, minimisation, and purpose limitation are built into the access layer, so data owners stay compliant by default.

Usage metering & settlement

Every access event is measured, priced, and reconciled, turning data usage into a transparent, billable commercial relationship.

Cloud-native deployment

Runs inside your existing cloud infrastructure. Data never has to leave its environment to be monetised.

Full audit trail

Every request, approval, and access event is logged, giving data owners and regulators a complete, verifiable record.

Commercial tooling

Pricing, contracts, and settlement are handled as part of the platform, not bolted on afterwards.

The boundary

Raw data never leaves the data owner.

Every participant runs a GateHouse container in their own environment. Models and queries travel to the data; only computed insights cross the boundary. Even the metadata GateHouse sees must pass the owner’s disclosure gate first.

metadata-only0 rows exported
How the cleanroom works
Sealed
Data owner
Snowflake
Sealed
Data owner
Databricks
Sealed
Data owner
Google Cloud
Governed resultΣ
raw rows touched: 0·insights returned: 1crossed
How it works

A governed path from raw data to realised value.

01

Register

Data owners register data products in place — in their own cloud environment — with usage policies and pricing attached.

02

Govern

Every request is evaluated against privacy rules, consent, and permitted purpose before any access is granted.

03

Access

Approved internal teams or external consumers query or receive only what governance allows — never raw, unscoped access to the underlying data.

04

Settle

Usage is metered automatically and value is settled back to the data owner, with a full audit trail for every transaction.

The platform

One system, the whole commercial workflow.

Governance, access, contracting, metering and settlement — in one platform, running in the cloud you already use.

Composition

Buyers describe an outcome in plain language. GateHouse composes a dataset across sellers, estimates coverage before you commit, and removes overlap so you never pay twice for the same record.

Cleanroom

Every participant runs a GateHouse container inside their own environment. Models and queries travel to the data, raw data stays in your environment, and only computed results cross the boundary.

Governance

Access is decided by jurisdiction, purpose, buyer classification and consent, written as policy-as-code. Run the same policy in enforcement or attestation mode, and state exactly what will and will not be released.

Settlement

Sellers define their own meters. GateHouse attributes what each source contributed and settles automatically, including drawdown against your cloud committed spend.

Agents

Specific agents for valuation, matching, negotiation, compliance, egress review and reconciliation. They run on metadata and inside containers, at the autonomy level you set: recommend, approve or autonomous.

Benchmarks

GateHouse profiles fill, freshness, width, consistency and stability inside the container. It then positions each dataset against the network on demand, benchmark and pricing.

For data owners

Two ways GateHouse creates value for the organisations that hold the data.

01

Participate in the data economy

Turn data you already hold into a governed, revenue-generating asset — without giving up control of it.

Governed, secure access to data
Every request is checked against policy and consent before any data is touched.
Fast commercials
Pricing, contracts, and settlement are built into the platform, so deals close in days, not quarters.
Built for AI workflows
Governed access designed for the model training and inference pipelines buyers actually run.
02

Unlock internal innovation

The same governed framework that powers external monetisation also puts data to work inside your own organisation.

Empower internal innovation
Give internal teams the same governed access framework used for external commercial deals.
Expand data use cases across the organisation
Surface data that's siloed today to new teams, products, and use cases.
Who it's for

Built for both sides of the data relationship.

For data owners

Realise the value of data you already hold

Monetise data without exporting or duplicating it
Keep full control over who accesses what, and why
Stay ahead of privacy and regulatory obligations by default
Get paid automatically as your data is used
For data owners
For data consumers

Access external datasets to power your AI and ML use cases in minutes

Access data products through a single, consistent framework
Know that every dataset is compliant and consent-checked
Pay for usage transparently, with no hidden procurement cycle
Integrate through standard cloud-native interfaces
For buyers
0rows exported
Your raw data never leaves your environment
3clouds
Snowflake, Databricks and Google Cloud — you use the one you already run
$600bn
Data monetisation market forecast by 2035. Sources, IDRIC and Fortune Insights
$49bn
AI model training market forecast by 2034. Sources, IDRIC and Fortune Insights
From the blog

Thinking, in the open.

All posts
Perspective

Move permissions, not data.

The future of enterprise AI is not built on moving data between organisations.

Oct 8, 2026 · 6 min read
Perspective

The commercial layer above the cleanroom.

Clean rooms solved secure collaboration.

Oct 1, 2026 · 7 min read
Engineering

Why we chose Cedar for policy-as-code.

We wanted governance claims that are provable, not merely tested.

Sep 24, 2026 · 8 min read

See what GateHouse can do for you.

Tell us about the data you hold and how you'd like to put it to work. We'll walk you through the framework and what deployment looks like in your cloud environment.