Editorial Policy

Why this page exists

Transparency about how content is made.

Colrows publishes technical writing about semantic execution, enterprise AI, governance, and the future of the data stack. Our readers - mostly CDOs, data architects, and platform engineers at regulated enterprises - rely on what we publish to make architectural decisions. They deserve to know how the work was produced.

This page documents our standards for authorship, AI use, sourcing, fact-checking, and corrections. It applies to every blog post, whitepaper, guide, and case study under colrows.com.

Authorship

Every piece is signed by a named human.

Every published article carries the byline of a Colrows team member who is accountable for its accuracy and point of view. Bylines link to the author's dedicated page on colrows.com (with biography and post archive) and to their LinkedIn profile.

We do not publish pseudonymous content. We do not publish AI-generated content under an AI pen name. We do not run author-less "by Colrows" posts on the blog (topic-index pages are clearly marked as such and do not claim authorship).

See our authors: Yogendra Sharma, Mayank Mudgal, Harshit Chouhan, Nilesh Kumar.

Use of AI

AI helps. Humans decide and own.

Colrows is a company that builds AI infrastructure, so it would be strange if we did not use AI tools in our own workflow. We do. Here is exactly how, and where the lines are drawn.

What AI is used for: background research on related work; surfacing prior art and citation candidates; drafting outlines; first-pass copyediting and grammar; generating alternate phrasings to choose between; producing inline SVG diagrams from authored specifications.

What AI is not used for: generating product claims that have not been verified against actual Colrows behavior; fabricating statistics, customer outcomes, or research citations; impersonating named authors; mass-producing low-effort pages to chase keywords.

Every article is reviewed end-to-end by its named author before publication. Technical claims about Colrows are cross-checked against the product documentation and engineering team. Customer outcomes are sourced from referenceable customer reports or anonymized case studies (the Cipla, SSP Group, and confidential BFSI numbers on this site, for example, are all from real engagements). Citations to third-party research (Gartner, MIT NANDA, Stanford HAI, McCrory, and so on) are checked against the original primary source, not summaries.

Sourcing standards

Primary sources, dated and linked.

• Research citations link to the originating publication or report (not aggregator summaries). Where a report is paywalled, we link to the official press release or excerpted page.
• Quotes from analysts (Gartner, Forrester, Stanford HAI, etc.) are sourced from the named publication and dated.
• Customer outcomes are sourced from real engagements. Where a customer is named (Cipla, SSP Group), they have approved the framing. Where a customer is confidential (the BFSI / ARC engagement), the numbers and architecture are accurate but the name is withheld at the customer's request.
• Competitive claims are sourced from each vendor's public documentation. We do not characterize a competitor based on hearsay or summarized takedowns.
• Dates on every article reflect either initial publication (datePublished) or the last material edit (dateModified). We do not back-date posts to inflate freshness.

Review process

Two passes before publish.

Every article goes through two reviews before it is published:

1. Technical review by an engineer familiar with the architecture being discussed. The goal is correctness: do the technical claims hold? Are the architecture diagrams accurate?
2. Editorial review by the named author for clarity, structure, and originality. The goal is that the post says something useful that does not already exist elsewhere on the internet.

An article is not published until both reviews are complete and the named author signs off.

Corrections

We update visibly, not silently.

If a published article contains a factual error, we correct the article in place, bump the dateModified field in the structured data, and note the correction at the bottom of the article when the change is material (numbers, citations, or claims). Cosmetic edits (typo fixes, link rot, image swaps) are made without a footnote.

To report a factual error, email dev@colrows.com with the article URL and the specific claim you are flagging. We respond within five business days.

Disclosure

Conflicts and sponsorships.

Everything published on colrows.com is produced by Colrows and reflects our point of view as a vendor in the semantic execution layer category. We disclose this implicitly through the domain and the byline, but it bears stating: we are not a neutral analyst, and our writing is informed by our product's architecture.

We do not publish paid placements, sponsored posts, or syndicated content from other vendors. We do not accept gifts or undisclosed compensation in exchange for editorial coverage of third-party tools.

Image and diagram credit

No generative AI imagery.

The diagrams on colrows.com are hand-authored inline SVG, written from architectural specifications and reviewed for technical accuracy. Photographs, screenshots, and customer logos are sourced from the original engagements with permission. We do not currently use generative-AI-produced imagery; if that changes, affected images will carry the IPTC DigitalSourceType metadata field set to TrainedAlgorithmicMedia, as Google recommends.