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For Technical Content Teams

Ship technical content in every language.
Review only what carries risk.

OTTO is an agentic AI platform for multilingual technical content. It works alongside your CCMS, TMS and AI to decide what each topic needs in every language: it classifies every change by risk, grounds translation in your termbase and translation memories, and scores every output, so only the work that needs expert judgment reaches your reviewers.

Safety content gets human eyes in every language. Routine updates ship on their own. Every decision stays on record.

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Release 4.2 · Installation guide
38 changed topics · 9 languages
Live
Classified
1 safety · 37 routine
RCC
Grounded
termbase + style rules
ALL
Scored
fluency · accuracy · consistency
97
Routed
1 topic to SME review
QEE
Approved
SME sign-off · logged 09:14
M.S-J
Works on your DITA as it is.
Markup, keys and conrefs come back intact, in every language.
The reality

Structure solved reuse. It didn't solve review.

Your CCMS knows which topics changed, where they're reused and which languages they ship in. It can't tell you which changes can go straight out, and which ones need an expert before they reach a customer, a technician or an AI assistant.

Every change takes the same road

A fixed typo in a UI label and a revised hazard statement go through the same review cycle and the same translation workflow. Your reviewers spend most of their time confirming what was never at risk.

AI writes faster than anyone can verify

GenAI drafts, rewrites and translates topics in seconds. Confirming that it kept your approved terms, your product names and your meaning still happens by hand, topic by topic. The writing got faster. The checking didn't.

One weak sentence ships everywhere

A source error doesn't stay put. It's reused across maps, translated into every locale and served back as an answer by your chatbot. A mistake used to cost one page. Now it costs every channel, in every language.

Where OTTO fits

OTTO meets your docs pipeline at every decision point.

User guides · API docs · release notes · instructions for use · safety messages · service manuals · knowledge bases · UI text

01 · Before production

Before anything runs, know what each topic needs.

When a release touches dozens of topics, OTTO assesses only the ones that changed, for risk, complexity, domain, content type and regulatory sensitivity, and sends each down the right path: automated, controlled AI or expert review. Unchanged topics stay as they are.

Safety & hazard messages

Warnings, cautions and safety instructions are flagged upfront and routed to expert validation, in the source and in every language.

Regulated information

Instructions for use, compliance statements and security information take the path with the tightest controls.

Release-driven updates

Routine changes from a product release take the automated path instead of waiting in the review queue.

High-volume, low-risk content

UI text, release notes and minor edits stop consuming the time your specialists need for everything else.

1 release → every changed topic classified → the right path for each
02 · During production

AI that writes and translates in your terminology, not its own.

Whatever model or MT engine you use, OTTO grounds its output in your termbase, translation memories, style rules and approved references. A deprecated term or an unapproved product name doesn't slip into forty topics and nine languages.

Terminology & product names

Approved terms stay in, deprecated ones stay out, across every topic and every language.

AI-assisted authoring

Drafts and rewrites grounded in your approved content, with your markup, keys and conrefs left intact.

Machine & LLM translation

MT and LLM output grounded in your translation memories and termbase, then adjusted by automatic post-editing before anyone reviews it.

Your models, your engines

Keep the LLMs and MT engines you already use. OTTO adds the controls around them.

1 termbase → every topic · every language · one voice
03 · After production

Score every output before it reaches a reader, or an AI.

Your documentation now feeds portals, chatbots and AI assistants as much as it feeds people. OTTO scores every output for fluency, accuracy and consistency, explains each score and recommends the next step: approve, review or reprocess.

Every language version

Each translated topic is scored against the source, not spot-checked by sampling.

Content that feeds AI

Topics served through portals, chatbots and AI assistants are scored before they're published.

Scores with reasons

Every score comes with its reasoning, so reviewers know exactly where to look.

Reprocess, don't restart

Output below your thresholds is re-run through the workflow instead of landing in someone's queue.

Every output → scored and explained → approved, reviewed or reprocessed
Already have AI in your CCMS?

Your CCMS manages the content. OTTO decides what it needs.

OTTO doesn't replace your CCMS, your TMS or your AI. It adds the decision layer between them: what can move on its own, what needs tighter control and what needs an expert.

CCMS + built-in AI CCMS + OTTO
When a topic changes Versioned and flagged for update. Every change looks the same. Classified by risk and complexity, then sent down the right path.
Review Everything goes to review, or someone decides by instinct what to skip. Reviewers get what carries risk or falls below your thresholds. Nothing else.
Across your stack Each tool has its own AI, its own settings and its own blind spots. One decision layer across your CCMS, TMS, MT engines and models, with the same thresholds everywhere.
Structure & reuse Generic AI rewrites can break markup, keys and conrefs, and someone fixes them by hand. Markup, keys and conrefs come back intact, in every language.
Audit trail Version history. Version history, plus the routing decision, the score and the approval for every topic.
The rules you answer to

The rules your documentation answers to.

Technical content is where products meet the law: safety messages, compliance statements, labeling and support documentation. In the US, each of them has to survive translation intact.

ANSI Z535.6

US standard for product safety information in manuals, instructions and collateral

What OTTO gives you Safety messages are identified before production and take the human-in-the-loop path, in English and in every translation. AI never gets the final word on them.

FCC · 47 CFR Part 15

Compliance statements required in the user manual of electronic devices

What OTTO gives you The Part 15 statements must sit prominently in every manual. OTTO's regulatory risk check flags them before production, and every version is scored against the source before it ships.

FDA · 21 CFR 801

Labeling rules for medical devices, including foreign-language labeling

What OTTO gives you If you translate labeling, every required statement must appear in that language too. OTTO scores each language version against the source and escalates what falls below your thresholds.

Section 508

Federal accessibility rules for ICT, including support documentation (36 CFR 1194)

What OTTO gives you Your docs must explain accessibility features and meet WCAG in electronic form. OTTO classifies those topics as regulated and scores every language version, so no market gets a thinner version.

California Prop 65

Consumer product warnings (27 CCR 25602)

What OTTO gives you If a label carries consumer information in another language, the warning must appear in that language too. OTTO flags warnings upfront and scores every language version against the English source.

Your stack. Your models. Your control.

Your CCMS stays. Your AI stays. OTTO adds the control.

OTTO works on DITA, XML or any format your pipeline produces, and gives it back with markup, keys and conrefs intact. It grounds production in your termbase and translation memories, reprocesses only the topics that changed, and connects to your CCMS, TMS and models through an API, an orchestration layer or on-prem. Your content stays in your environment and is never used to train our models.

Talk to our team →
500+
enterprise customers served
60+
seamless integrations
40
years in the language industry
FAQ

Straight answers for documentation teams.

Something specific to your stack? Talk to our team and we'll walk through it.

Our CCMS already has AI. Why would we add OTTO?

Because they answer different questions. Your CCMS and its AI help you write, reuse, find and publish content. OTTO decides what each topic needs before it ships: it classifies every change by risk, grounds production in your terminology, scores the output and sends only what needs an expert to review. It works with the CCMS, TMS and models you already have, and replaces none of them.

Does OTTO work with DITA and other structured formats?

Yes. OTTO works on structured content as it is, in DITA, other XML or any format your pipeline produces. Markup, keys and content references come back intact, so reuse keeps working in every language and nothing has to be rebuilt by hand.

How does OTTO decide what needs human review?

Before anything runs, OTTO assesses each piece of content for risk, complexity, domain, content type and regulatory sensitivity. You set the thresholds. Low-risk content takes the automated path, medium-risk content the controlled AI path, and high-risk content like safety messages goes to expert review.

Will AI respect our terminology?

Yes. OTTO grounds every output in your termbase, translation memories, style rules and approved references, using retrieval and a knowledge graph, so terminology, tone and regulatory wording stay consistent across topics and languages.

How is OTTO different from a content quality checker?

A checker tells you what's wrong once the content exists. OTTO decides the path before production begins, grounds the work while it runs, then scores the output and recommends the next step: approve, review or reprocess.

Does OTTO replace technical writers?

No. It takes routine verification off their plate, so writers, SMEs and reviewers spend their time on the content where their judgment matters most.