SilaCities/Transparency
STransparency

What we disclose, and who to write to if we are wrong.

Urban intelligence only earns trust by showing its working. Here are our public commitments. What we disclose, where you can audit, and how to raise a concern.

01 · ReviewQuarterlyDisclosures refreshed
02 · Paid placementNoneNo sponsored content, ever
03 · Data-sharingOffBetween deployments by default
04 · DisclosurePublicCorrections, conflicts, sources
01Commitments

Six public commitments.

What we disclose by default, and what you can audit on request.

01

Data provenance

Every ingested dataset is tagged with its source, licence, and last refresh date. Deployment teams can audit the full source list and refresh cadence on request.

Per-deployment audit
02

Known limits

We publish the known limits of each model and dataset. Where coverage is thin, where latency matters, where confidence is low. "Not enough signal here" is a valid answer.

Honest refusals
03

Model disclosure

Architectures, training-data provenance and performance benchmarks are documented. Under NDA we share the full technical methodology for audit or procurement review.

NDA-shared
04

Data isolation

Every deployment is strictly isolated. No cross-client queries, no shared databases, no data used to train shared models without explicit written consent.

No crossover
05

Funding and partnerships

We disclose funding sources and strategic partnerships in company filings. Client engagements that inform published articles are disclosed in the article footer.

Company filings
06

Corrections and retractions

We correct publicly and inline, every time. Retractions stay on the page with an explanation. See the editorial policy for full process.

Public record
02Disclosures

Standing disclosures.

Ongoing commitments that apply across every engagement, every article, every deployment.

FundingPrivateSila Artificial Intelligence Research LLC is a privately held company. Investor disclosures on request under NDA.
Commercial relationshipsDisclosed per-engagementEvery published case study names the client and, where applicable, the consulting partner. We do not publish anonymised client wins.
Paid placementNoneWe do not accept payment for editorial coverage or placement. We do not run sponsored content.
Data-sharingNone between deploymentsClient data is never used to train shared models. No anonymised or aggregated data crosses deployment boundaries without explicit written consent.
03Raise a concern

Where to write, about what.

Five direct addresses. No forms, no gatekeeping.

01

Concerns about a published claim

editorial@silacities.com, see /editorial-policy for the correction process.

02

Concerns about data handling or privacy

privacy@silacities.com, see /privacy for our data policy.

03

Security disclosures

security@silacities.com, we operate a coordinated disclosure policy.

04

Legal and regulatory enquiries

legal@silacities.com

05

Whistleblower and ethics concerns

ethics@silacities.com, handled confidentially.

04Under review

In procurement, audit or regulatory review? We'll share more.

For formal audit, procurement or regulatory review we share the full technical methodology, source-list inventory and model performance benchmarks under NDA. Talk to the research team to scope what is needed.

Direct line · Governance

Contact governance

For formal audit, compliance, or disclosure review.

Research
research@silacities.com
Legal
legal@silacities.com
Ethics
ethics@silacities.com
Response
2 business days