diff --git a/content/docs/processes/field_imagery.md b/content/docs/processes/field_imagery.md
index a0870eb..26045c1 100644
--- a/content/docs/processes/field_imagery.md
+++ b/content/docs/processes/field_imagery.md
@@ -6,7 +6,7 @@ next: /docs/dissemination/
 
 ## The Mission
 
-Commercial street-level imagery is often locked behind restrictive licenses, proprietary viewers, and paywalls, making it inaccessible for researchers, urban planners, and the general public. We are building a sovereign, open-source alternative for Canada.
+Commercial street-level imagery is often locked behind restrictive licenses, proprietary viewers, and paywalls, making it inaccessible to our target audience. We are building a sovereign, open-source alternative for Canada.
 
 By self-hosting a **[Panoramax](https://panoramax.fr/)** instance, we provide a decentralized platform where field imagery is treated as a public utility: fully downloadable, API-accessible, and privacy-compliant.
 
@@ -14,9 +14,8 @@ By self-hosting a **[Panoramax](https://panoramax.fr/)** instance, we provide a
 
 ## The Infrastructure
 
-Our field imagery pipeline is built on the **Panoramax** ecosystem, a federated open-source alternative to Google Street View. Instead of relying on centralized corporate servers, we operate a sovereign instance that guarantees data permanence and open access.
+Our field imagery pipeline is built on the **Panoramax** ecosystem, a federated open-source alternative to Google Street View that guarantees data permanence and open access. 
 
-* **Platform**: Self-hosted Panoramax instance running on our internal infrastructure.
 * **Storage**: High-performance object storage backend for hosting terabytes of 360° and flat field imagery.
 * **Federation**: Our instance connects to the global Panoramax federation, ensuring that while the data is hosted in Canada, it is discoverable worldwide through the global panoramax catalog.
 
@@ -28,8 +27,8 @@ We treat field imagery as a data engineering challenge, ensuring "time-to-insigh
 
 1. **Ingestion**: Raw imagery is captured using diverse hardware (ex. 360° cameras, mobile rigs, meta glasses, etc.) and ingested by our systems. 
 2. **Privacy & Anonymization**: Before publication, all imagery undergoes a rigorous privacy scrub. We utilize automated detection pipelines to blur faces and license plates, ensuring compliance with Canadian privacy standards while maintaining data utility.
-3. **Standardization**: Images are processed into standardized, web-optimized tiles for the viewer and high-resolution archives for analysis.
-4. **Metadata Extraction**: We extract and normalize/strip EXIF and GPS telemetry, indexing it into a **[FAIR Catalog](https://stac-utils.github.io/stac-geoparquet/latest/spec/stac-geoparquet-spec/)** compliant API.
+3. **Standardization**: Images are processed into systems-ready formats, making it ready for analysis.
+4. **Metadata Extraction**: We extract and normalize/strip identifiying information (ex. EXIF and GPS telemetry), indexing it into a **[FAIR Catalog](https://stac-utils.github.io/stac-geoparquet/latest/spec/stac-geoparquet-spec/)**.
 
 ---
 
@@ -40,4 +39,3 @@ Unlike commercial platforms that only offer a "view" of the data, we provide the
 * **API Access**: Full programmatic access via the Panoramax REST API for querying imagery by location, date, or sequence.
 * **Bulk Datasets**: Curated dumps of street-level imagery available for computer vision training, asset management, and change detection models.
 * **[FAIR Data Catalog](https://stac-utils.github.io/stac-geoparquet/latest/spec/stac-geoparquet-spec/) Integration**: Seamless integration with geospatial workflows (ex. DuckDB, QGIS, Python, R, Julia, etc.).
-`