Tone of Voice Consistency
I build AI agents that make your documentation read as though one person wrote it -- enforcing style guides, standardising terminology, and aligning tone across everything from internal wikis to customer-facing help centres.
Enforcing your style guide at scale
Style guides only work if they're consistently applied. Manual enforcement doesn't scale.
Every organisation with a style guide faces the same problem: people don't read it, and even those who do can't remember every rule while they're focused on writing content. I build agents trained on your specific style guide that review content in real time or in batch, catching deviations and suggesting corrections. They handle everything from heading capitalisation conventions to preferred sentence structures -- the accumulated details that make documentation feel polished and professional.
Custom Style Rule Engine
I configure agents with your complete style guide -- not just grammar rules, but your specific preferences for capitalisation, punctuation, list formatting, heading hierarchy, number formatting, date conventions, and more. Every organisation has its own standards; the agent learns and enforces yours, not a generic set.
Real-Time Writing Assistance
Agents that integrate into your documentation workflow and provide feedback as content is written. Authors see suggestions immediately, learning your style conventions through practice rather than reading a guide. Over time, this feedback loop improves writing quality at the source -- not just in post-publication review.
Batch Content Review
For existing documentation that predates your style guide, I deploy agents that audit your entire content library and produce prioritised reports of style violations. High-traffic pages with significant deviations get flagged first. The agent can also generate corrected versions for review, dramatically reducing the manual effort of bringing legacy content into compliance.
Style Guide Evolution
Style guides aren't static. As your organisation evolves, so do your conventions. I build agents that track style decisions made during reviews, identify patterns in approved exceptions, and recommend style guide updates. Your guide stays a living document that reflects actual practice, not an outdated ideal.
Standardising terminology across your documentation
When the same thing has three different names in your docs, nobody trusts any of them.
Terminology drift is one of the most common and most damaging documentation problems. A product gets referred to by its code name, its marketing name, and an informal abbreviation -- all in the same wiki. Technical concepts get explained with different words by different authors. I build agents that map your terminology landscape, identify inconsistencies, and systematically bring everything into alignment with your approved vocabulary.
Terminology Discovery & Mapping
The agent scans your entire documentation corpus and builds a map of every term, acronym, and product name in use -- along with its variants. You see exactly how many different names exist for the same concept, which variants are most common, and where each one appears. This map becomes the foundation for standardisation decisions.
Controlled Vocabulary Management
I build and maintain a controlled vocabulary -- your single source of truth for approved terms. The agent manages synonyms, deprecated terms, and context-specific usage rules (e.g., using the full product name on first mention, then the abbreviation). This vocabulary integrates directly into your content review workflow.
Automated Term Replacement
Once you've approved the standard terms, the agent can systematically update existing content -- replacing deprecated terminology with current equivalents across your entire documentation library. It handles context sensitivity, ensuring replacements are appropriate (not every instance of "platform" means the same thing) and producing change reports for review.
Glossary Generation & Maintenance
The agent automatically generates and maintains a glossary from your controlled vocabulary, complete with definitions, usage examples, and cross-references. This glossary stays current as terminology evolves, and can be published as a standalone resource or embedded contextually throughout your documentation.
Readability and brand voice alignment
Clear writing that matches your brand builds trust. Inconsistent, dense writing erodes it.
Documentation that's technically accurate but hard to read fails its purpose. I build agents that assess content readability against your target audience, identify passages that are unnecessarily complex, and suggest clearer alternatives -- without dumbing down technical content. For customer-facing documentation, I extend this to full brand voice alignment, ensuring your help centre, API docs, and product guides all feel like they come from the same organisation.
Audience-Calibrated Readability
Readability isn't one-size-fits-all. Developer documentation has different standards than end-user help articles. I configure agents with audience profiles -- technical level, domain familiarity, reading context -- so readability scoring reflects your actual readers, not a generic formula. Content that's too complex for its audience gets flagged with specific improvement suggestions.
Sentence & Paragraph Optimisation
The agent identifies specific readability problems: sentences that are too long or structurally complex, paragraphs that try to cover too many ideas, passive constructions that obscure who does what, and jargon that hasn't been defined. Suggestions preserve technical accuracy while improving clarity -- making content easier to scan, understand, and act on.
Brand Voice Profiling
I train agents on your brand voice guidelines and examples of content that embodies them well. The agent then evaluates new and existing content against this voice profile -- checking tone, formality level, directness, and personality markers. Documentation that drifts from your brand voice gets flagged with specific, actionable feedback.
Consistency Scoring & Dashboards
Track voice consistency across your entire documentation library with aggregate scoring. I build dashboards that show consistency trends over time, identify sections or contributors that need attention, and measure the impact of style enforcement efforts. This gives documentation managers the visibility they need to maintain quality at scale.
Ready to make your documentation sound like one voice?
Tell me about your style challenges and I'll outline an approach to bring consistency to your content.