24 years in scholarly & STM publishing production — now applied to enterprise AI
AI output your enterprise can actually stand behind.
The same zero-tolerance review discipline we built for scholarly publishing now backs every AI output we deliver: 200 trained human reviewers and ISO 27001 / ISO 9001:2025-certified quality systems check everything before it ships.
All certifications independently audited. Documentation available on request.
Where this discipline comes from
We didn't start as an AI company. We started as the vendor scholarly publishers couldn't afford to be wrong.
Since 2002, Transforma has handled manuscript-to-XML production, JATS schema compliance, and MRW-enabled peer-review support for academic and STM publishers — content where a dropped Greek letter or a broken citation cross-reference isn't a minor bug, it's a published error a journal has to correct in print.
That's the same zero-tolerance review discipline behind our Human-in-the-Loop model today. We didn't adopt tiered quality review when AI made it fashionable — we've been running it for twenty-four years, on work with no tolerance for “mostly” correct.
24 years · Chennai-founded · 200-person team · 100% client retention since inception
Who trusts us with quality-critical work
We work with scholarly publishers and research organizations who can't afford a vendor's mistake becoming their author's, editor's, or society's problem. Client logos available on request — most of our agreements include confidentiality terms we take as seriously as our SLAs.
Two engines. One accountable system.
Every output from either engine passes through the same review layer below — it's never sold as an unchecked add-on.
AI doesn't get the final word here. A trained reviewer does.
A tiered review process stands between every AI output and your team — built on 24 years of catching what automation misses.
See how review worksISO 27001 + ISO 9001:2025 certified. Independently audited, not self-declared.
Built on precision. Applied where precision matters most.
Two decades of quality-critical delivery in publishing and research — now extending the same discipline into five new regulated industries.
Data in. Human validation. AI output. Nothing skips the middle step.
Sourced, structured, and staged for review — not shipped raw.
Tiered escalation for anything a model shouldn't decide alone.
AI-ready, schema-compliant, and accountable to a named process.
Results we can show our work on.
We're finalizing our first published case studies with client sign-off — we don't publish a number we can't back with their approval.
In the meantime, ask for a reference call. We'll connect you directly with someone who's worked with us.
Request a reference callBuilt on real infrastructure, not a slide.
A three-person in-house AI/ML team, building on open-source LLMs, deployed on AWS. Small, honest about its size, and growing every quarter.
See our technology →Security you can verify.
ISO 27001-certified information security management. Independently audited, not self-declared.
See our security posture →Covers how we handle, store, and process client data across every engagement.
Covers the process discipline behind every deliverable — from a single dataset to a full production pipeline.
Quality you can audit.
ISO 9001:2025-certified quality management, independently audited on the same schedule as our security certification.
Request documentation →“We'd rather connect you with a real client than write our own quote.”
We don't publish testimonials we can't attribute, and we don't attribute quotes without a client's permission. If you're evaluating us seriously, ask for a reference call.
What we're learning, publicly.
Notes on AI data quality, human review, and enterprise AI operations — from the team doing the work.
First post: “Why the last 20% of a dataset is the only part that matters.”
Visit Insights →Ready to see the review process for yourself?
Thirty minutes with our team. No generic pitch — we'll walk through your actual workflow.