# Onymos Brand Voice

> Authoritative, precise, and operationally focused.

## Positioning
Onymos provides an intelligent intake layer for healthcare and life sciences organizations. It automates the capture and validation of complex clinical documents to eliminate errors at the source and accelerate laboratory throughput.

## Voice principles
*   **Direct:** Uses short, punchy sentences that prioritize clarity over flourish.
*   **Outcome-oriented:** Focuses on the immediate business result, such as faster reimbursement or reduced rework.
*   **Technical and Secure:** Employs industry-specific terminology (TRFs, LIMS, RCM) to establish credibility with clinical and security stakeholders.
*   **Active:** Uses strong verbs like "Eliminate," "Stop," "Ingest," and "Govern" to demonstrate software capability.

## Tone by context
| Context | Tone |
|---|---|
| Marketing Hero | Urgent and solution-focused: identifying a pain point (revenue loss) and offering an immediate fix. |
| Product Features | Technical and functional: explaining how the "intelligent intake layer" interacts with data and infrastructure. |
| Compliance/Security | Reassuring and absolute: emphasizing certifications and "inside your infrastructure" deployment. |
| Customer Stories | Collaborative and scalable: focusing on "hyperscaling" and partnership. |

## Lexicon
- **Use:** Intelligent intake, intake layer, lab-native, rework, throughput, turnaround time (TAT), structured and unstructured data, revenue loss, downstream systems.
- **Avoid:** Not evident from captured copy (though the brand avoids generic "AI" buzzwords in favor of specific terms like "Nucleus" or "Cognitive Insight Model").

## Messaging do's and don'ts
*   **Do:** Link technical features directly to operational benefits (e.g., "Clean data. No rework.").
*   **Do:** Emphasize that the solution lives "inside your infrastructure" for security.
*   **Do:** Use industry acronyms (HIPAA, SOC 2, TRFs) to signal expertise.
*   **Don't:** Use flowery or metaphorical language; keep descriptions literal and grounded in laboratory workflows.
*   **Don't:** Focus on the "cloud" generally; focus on the "customer's boundary" and data privacy.

## Evidence
*   "Eliminate intake errors before they become revenue loss."
*   "Clean data. No rework. Faster reimbursement."
*   "Build your intelligent intake layer."
*   "DocKnow understands context, relationships, and terminology specific to precision medicine."
*   "From a security perspective, there was really no concern because there is no data leaving the customer’s boundary."