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TECHNOLOGY / SYSTEMS & PROCESS

Connecting data and work:
the foundation for AX.

Data collection and validation, workflow automation and traceable decision support.
Explore the software foundation connecting daily operations, and our content creation technology.

AX · From data to work

For AI to be useful,
work needs connected context.

We connect data across tasks and automate repetitive processing.
Summaries and suggestions are designed to retain evidence for people to review.

Connected data

We retain originals collected through files, APIs and browsers, then organize and validate them against shared standards. We manage how products, orders, inventory and settlements connect.

Connected execution

We assign jobs around schedules and resources, and track status, failures and retries. Our own operating foundation connects each stage of the work.

Traceable decisions

We build paths from metrics, reports and AI suggestions back to original evidence. We validate scope for each workflow and record human reviews and decisions.

CDH operational data and ioCAST production data are handled within each service’s responsibilities and permissions. The production diagram below does not describe all of CDH.

CONTENT PRODUCTION / SYSTEM ARCHITECTURE

Separate responsibilities.
Connected sources and outputs.

Storage handles files. Engines handle production.
ioCAST handles review and selection.

01 / INPUT

Source files

Recorded video · Photos · Audio

Production assets as files

02 / STORE

Dropfile

Files · Versions · Checksums

Pass source references

03 / MAKE

Production tools

EngineScript → Cuts & captions → Render

AI musicStyle & lyrics → Audio candidates

04 / REVIEW

ioCAST

Review frames, captions and evidence

Compare candidates → Human selection

05 / OUTPUT

Selected output

Video · Music · Thumbnails

Export · Storage references

This diagram explains responsibilities and data connections. It does not show live job status.

↳ Selected outputs are stored in Dropfile and linked back to the sources used in production.

Verified product information · Brand materialsEvidence for Engine production and ioCAST review

02 / VIDEO PIPELINE

One video.
Six production stages.

From input to final frame,
we connect the information each stage records.

  1. 01

    Fix inputs and production criteria

    We link recorded assets, product descriptions, brand voice, logos and profile versions to the production request. We define the materials and purpose first.

    Assets · Products · Profiles
  2. 02

    Analyze scenes and find evidence

    We analyze recorded scenes and find product and brand materials for the script. Source references and verified information remain linked as production evidence.

    Scene information · Evidence
  3. 03

    Build script and caption candidates

    We compose text from product information and assets. We are improving review of the sequence and role of the whole piece, alongside individual claims.

    Copy sets · Caption candidates
  4. 04

    Arrange cuts, captions and audio

    We combine scene order and duration, caption placement and music segments. Music is selected through a separate generation and listening workflow, then linked to the video.

    Timeline · Audio
  5. 05

    Render and inspect actual frames

    We render with Remotion- and FFmpeg-based tools. We inspect final captioned frames, crops and zooms, and prepare outputs such as thumbnails.

    Video · Frames · Thumbnails
  6. 06

    Compare, select and retain history

    People review candidates in ioCAST and select an output. Production runs, source references and output files are linked for later retrieval.

    Selected output · Production history
Clip analysis · In development

We are improving clip analysis and scene selection. We reuse shared analysis of the same file while keeping product-specific assessments separate, and are preparing a library for reusing crop, zoom and speed variants.

03 / JUDGMENT & EVIDENCE

What does an assessment check,
and what does it record?

Improving & validating
  1. 01

    Match copy to product information

    We check claims against verified product information and figures. We look for unsupported statements about materials, performance or benefits that scenes alone cannot establish.

    Facts · Figures · Sources
  2. 02

    Overall flow and each sentence’s role

    We review the order and role of the complete caption set, checking for contradictions, unnecessary repetition and wording that conflicts with the product context.

    Context · Sequence · Repetition
  3. 03

    Match wording to the actual render

    We review captions alongside actual scenes. We inspect the rendered output to check whether crops, zooms and caption placement suit the selected wording.

    Scenes · Crops · Captions
  4. 04

    Warnings and human judgment

    We have defined warning categories for exaggerated or prohibited wording, implied medical benefits and unsupported figures. We evaluate missed risks alongside unnecessary warnings.

    Warnings · Evidence · Revisions & selection
Final checks for advertising use

People verify evidence for claims, required advertising disclosures and channel and industry standards. An absence of warnings does not guarantee approval or factual accuracy.

04 / COLLECTION & FILE PROCESSING

Files and APIs
enter through different paths.

Files connect through storage references.
API and web data connect directly to processors.

A / Direct connection

Collected data without a file upload

DIRECT INPUT

API · Web · Blogs

Authenticated API responses

Collect text, media and sources

PROCESS

Data processing

Organize fields · Parse · Validate

Retain source and original information

USE

Product information

Lookups · Production evidence

Connect verified information to production

This diagram shows data paths, not live job status.
B / File-based

Three routes from shared storage, depending on purpose

Select a route to replay its flow.
SOURCE / MEDIA

Video · Image · Audio

Source assets for production

SOURCE / DATA

Excel · CSV · Images

Product data · OCR images

SOURCE / FILE

CSV · TXT · Excel

Files for encoding conversion

STORE & REFERENCE

Dropfile

File storage · Versions · Checksums

Pass file references without interpreting content

MAKE

Engine · Music production

Scene analysis · Editing · Generation

READ

Data processing · OCR

Parse · Extract text · Validate

CONVERT

File converter

Detect encoding · Convert formats

OUTPUT & REUSE

Reusable outputs

Production candidatesioCAST review → Store selected outputs

Product information to verifyCheck against originals → Lookups and production materials

Converted filesDownload → Clean up temporary storage

↳ Store production outputs and converted files againThis diagram shows data paths, not live job status.
INPUT

Video · Image · Audio

Source assets for production

  1. STOREDropfile

    File storage · Pass references

  2. PROCESSEngine · Music production
  3. OUTPUTProduction candidates

    ioCAST review · Store selected outputs

INPUT

Excel · CSV · Images

Product data · OCR images

  1. STOREDropfile

    File storage · Pass references

  2. PROCESSData processing · OCR
  3. OUTPUTProduct information to verify

    Check originals · Lookups and production evidence

INPUT

CSV · TXT · Excel

Files for encoding conversion

  1. STOREDropfile

    File storage · Pass references

  2. PROCESSFile converter
  3. OUTPUTConverted files

    Download · Clean up temporary storage

↳ Dropfile stores originals; processors interpret them. Production outputs and converted files link back to storage.

Storage and interpretation boundaries

Dropfile stores files; dedicated processors handle parsing, OCR and conversion. Photo OCR results are checked with originals and sources, and people review suggested categories and fields. API integrations align service authentication and received fields.

Current product input scope

Collection, OCR and API integration are existing capabilities. ioCAST product registration focuses on file uploads and text entry; direct import from product URLs is not currently available. CSV and TXT encoding conversion and CSV extraction from Excel’s first data sheet use a separate file processing workflow.

05 / STORAGE FOUNDATION

Dropfile.
Through every file state.

We store source video, images, music, finished outputs and thumbnails,
and manage the file lifecycle from upload to restoration.

01

Multipart uploads · Retries

We split large uploads and track progress. Retained upload parts support continued retries.

02

Versions · Checksums

We manage file sizes, versions and checksums to link production sources and outputs to the exact files used.

03

Previews · Thumbnails

We provide previews for supported formats and thumbnails for images and video. Thumbnail processing status and failures are tracked too.

04

Trash · Version restoration

Deleted files and previous versions can be restored according to file state and retention policy.

05

Batch actions · Downloads

People can select multiple files for processing and prepare batch downloads. Long jobs such as compression expose their status.

06

Authenticated storage API

APIs connect uploads, lookups and downloads. Access controls distinguish file owners and administrators.

06 / EXECUTION & ACCESS

The scheduler coordinates
job order and resources.

Queue & priorities implemented · Integration validation
REQUEST

Request & queue

Request video and voice jobs

Add to queue

SCHEDULE

Priorities · Resources

Adjust job order

Assign available resources

EXECUTE

Execution · Status tracking

Execution, interruption and completion history

Verify uncertain termination

RECORD

Results · History

Store output files

Link requests and execution records

This diagram explains responsibilities and data connections. It does not show live job status.

Verify execution before moving on

We coordinate GPU resources and job order for video and voice work. The design holds subsequent execution until a job with uncertain termination has been checked.

Organization scope and request permissions

We check permissions for sessions and API requests, separating data access by organization. Shared account and tool integrations are being prepared to preserve permissions and execution history.

Asset usage terms and records

We manage filmed participants, contract materials and usage periods, and record assets and contract information used in each request. File versions and production runs are tracked together.

This does not mean every product runs automatically in production. Integration and activation are verified separately for each consuming service.

VOICE & MUSIC

Voice, sentence by sentence.
Music, by mood and segment.

We design the two production workflows separately
and connect them on the video timeline.

Shared API and catalog built · Full production integration in progress

Narration

  1. Text & pronunciation

    We distinguish on-screen text from spoken text. A dictionary manages pronunciation for proper names and units.

  2. Sentence generation and reuse

    We record voices and generation settings, storing audio by sentence. We are connecting a workflow to regenerate only the sentences needed and reuse outputs.

  3. Synthesis and quality validation

    We have tested voices, delivery styles and sentence joins. Voice consistency in long scripts, pronunciation, silence and duration require further validation.

Full narration production is not generally available yet. We are validating scheduler and ioCAST integration as we apply it.

ioCAST music production

Music generation and LoRA

  1. Style · Lyrics · Vocal direction

    Mood, style, lyrics and vocal settings guide the generation of audio candidates.

  2. Optional LoRA

    Compatible music generation routes let people select a LoRA and its strength. They can listen to and compare the result with base generation.

  3. Segment selection and usage history

    People use waveforms to inspect segments and select music for video. Usage counts and recent usage history are available.

Music LoRA is separate from training or tuning assessment technology. It does not imply better quality across all styles.

07 / DEVELOPMENT & NEXT

What we are refining now.
What we will connect next.

Development stage and availability are stated separately.

Implemented · Production status being verified

Preview work in progress

We have developed an interface for listening to selected music and distinguishing edits in progress from the original output.

Merge verified on 2026-10-23 · Production deployment requires separate verification
Development · Evaluation

Technology adapted to the task

We compare results on fixed materials and review quality and resource use. Content, format, processing time and failures are considered together; actual frames and listening results determine where to apply the technology.

Future direction

MCP connects tools and data

We are preparing connections for conversational AI to query permitted data and call production tools. Starting with read-focused validation, we plan to expand to authorized production requests while preserving user and organization permissions and execution history. Production-specific tuning and proprietary technology research are also planned.

Longer-term direction

Beyond production

We aim to extend into long-form production, channel and advertising integration, and feeding results into future planning. Our own information and partner-content channels are being prepared as internal operating projects.

Existing management features · Expansion planning

Carry brand standards forward

ioCAST brand profiles manage the identity and standards used in production. Broader brand asset management is being prepared as a separate plan.

Recommendation foundation built · Product integration in progress

Technology for understanding products

We provide reference information for reviewing product size, fit and measurement differences between sizes. Product interface integration is in progress; final checks use physical samples and fittings.

Based on documents reviewed on 2026-10-24. Availability will be communicated after feature-specific integration and validation.

The next step in how you work

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