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Documentation Index

Fetch the complete documentation index at: https://api-docs.ollang.com/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

The Ollang Project Management Dashboard supports both:
  • AI-only workflows,
  • and AI + Human Review workflows.
This allows organizations to:
  • fully automate localization,
  • integrate internal reviewers,
  • assign external linguists,
  • onboard dubbing studios,
  • or combine AI and human review pipelines.
The workflow selected during Order creation determines:
  • how the Order is processed,
  • who can review it,
  • and how final delivery occurs.

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Workflow Types

AI-only Workflow

Fully AI-generated localization workflow that remains editable and assignable after generation.

AI + Human Review Workflow

Workflow where human linguists or editors review, refine, and deliver the generated output.

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AI-only Workflow

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Overview

AI-only workflows generate localization outputs using AI orchestration pipelines without automatically assigning a human reviewer. However:
  • AI-only Orders remain editable,
  • rerunnable,
  • and assignable after generation.
This means organizations can still:
  • internally review outputs,
  • assign linguists later,
  • or reprocess workflows if needed.

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AI-only Workflow Behavior

Source Asset
        ↓
AI Processing
        ↓
Generated Output
        ↓
Editable / Assignable / Downloadable

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Important Clarification

AI-only does not mean the Order is locked or non-editable.
Project Management Users can still:
  • edit outputs,
  • rerun workflows,
  • assign editors,
  • assign linguists,
  • or deliver outputs manually.

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AI + Human Review Workflow

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Overview

AI + Human Review workflows combine:
  • AI-generated localization,
  • with human editing and review operations.
This workflow is commonly used for:
  • enterprise localization,
  • accessibility workflows,
  • high-visibility media,
  • regulated industries,
  • and premium localization pipelines.
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AI + Human Review Pipeline

Source Asset
        ↓
AI Processing
        ↓
Human Assignment
        ↓
Editing / Review
        ↓
Final Delivery

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Human Review Assignment Logic

Human review assignments will involve Ollang-managed reviewers. Organizations can request human review support from Ollang.

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Example Assignment Workflow

Project Manager creates Order
        ↓
AI generates output
        ↓
Ollang's Project assigns the order to a Linguist
        ↓
Linguist edits and delivers Order

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Editor Interface

Editors and linguists perform operational review inside the:
  • Editor Interface.
The Editor Interface supports:
  • subtitle editing,
  • transcription editing,
  • timing adjustments,
  • dubbing review,
  • speaker management,
  • and multilingual delivery operations.

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Subtitle Editing Capabilities

Editors can:
  • edit subtitle text,
  • modify timing,
  • split subtitle segments,
  • merge subtitle segments,
  • optimize CPS/CPL,
  • adjust readability,
  • and refine localization quality.

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Dubbing Editing Workflows

For AI Dubbing workflows, editors can:
  • review generated translations,
  • refine dialogue,
  • optimize pacing,
  • modify localized text,
  • and rerun synthesis workflows.
Depending on the workflow:
  • resynthesis (Text-To-Speech Operations) may occur after edits.

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Segment-Level Editing Behavior

If a subtitle or dubbing segment is split:
  • edits operate at segment level.
Example: 
Original segment:
"Welcome to the platform."

Segment split into:
- "Welcome"
- "to the platform."

If one segment changes later:
- only the edited segment may require regeneration.

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Human Delivery Workflow

After editing is completed:
  • editors or linguists deliver the Order.
Delivery updates:
  • Order status,
  • Project visibility,
  • and downstream operational workflows.
The finalized outputs then appear inside:
  • the Project Management Dashboard.
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Review Visibility Rules

Project Management Users generally have visibility into:
  • all organizational Projects,
  • all Folders,
  • and operational workflows.
Editors and linguists only see:
  • explicitly assigned Orders.

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Example Visibility Structure

Folder contains:
- 10 Projects
- 200 Orders

Editor assigned:
- 5 Orders

Result:
- Editor only sees assigned Orders.

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AI QC and Human Review

Human review workflows may operate alongside:
  • AI QC evaluation,
  • QC thresholds,
  • and workflow automation rules.
Organizations may configure workflows such as: 
If QC score < threshold
        ↓
Automatically assign linguist
This enables:
  • scalable review operations,
  • automated escalation,
  • and multilingual QA workflows.
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Rerun Workflows

Orders may be rerun after:
  • subtitle edits,
  • workflow changes,
  • translation refinements,
  • or synthesis adjustments.
Rerunning may regenerate:
  • subtitles,
  • translations,
  • dubbing outputs,
  • or downstream deliverables.
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Studio Dubbing Review Workflows

Studio Dubbing workflows support:
  • externally managed recording operations,
  • uploaded dubbing assets,
  • and final delivery coordination.
Studios may:
  • upload final mixes,
  • upload dubbing vocals,
  • or coordinate delivery assets inside the platform.

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AI QC Evaluation

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Overview

AI QC Evaluation allows Project Management Users to automatically evaluate subtitle localization quality using configurable AI-based quality assessment. This workflow is currently available for:
  • Subtitle Translation Orders.
The feature helps organizations:
  • evaluate localization quality,
  • identify linguistic weaknesses,
  • benchmark translation performance,
  • and improve multilingual consistency before delivery.

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How AI QC Evaluation Works

Project Management Users can run an AI-powered quality evaluation directly from the Order interface.
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Workflow: 
Subtitle Order
        ↓
Click "QC Evaluation"
        ↓
Configure Evaluation Settings
        ↓
Select Model + Prompt
        ↓
Run Evaluation
        ↓
QC Results Generated
The system evaluates subtitle quality based on:
  • predefined evaluation criteria,
  • optional custom criteria,
  • selected evaluation model,
  • and prompting instructions.

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Default Evaluation Criteria

The platform currently includes four built-in evaluation dimensions:

Accuracy

Evaluates whether the translation preserves the intended meaning of the source content.

Fluency

Evaluates readability, grammar, and natural language quality.

Tone

Evaluates whether tone, voice, and intent remain consistent with the original content.

Cultural Fit

Evaluates whether localized content feels contextually and culturally appropriate for the target audience.

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Custom Evaluation Criteria

Organizations may optionally define:
  • custom evaluation criteria.
This allows teams to evaluate content based on:
  • brand guidelines,
  • legal requirements,
  • subtitle standards,
  • accessibility expectations,
  • or domain-specific localization rules.
Example: 
Custom Criteria:
"Medical Terminology Compliance"

Prompt:
Evaluate whether approved medical terminology was consistently preserved.

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AI QC Results

Once evaluation is completed: The system generates:
  • QC scoring,
  • evaluation reasoning,
  • criteria-level analysis,
  • and quality observations.
These results help organizations:
  • validate localization quality,
  • identify problem areas,
  • and decide whether human review is required.
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Human QC Annotation

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Overview

Human QC Annotation enables linguists and editors to evaluate AI-generated subtitle output using structured quality tags. Unlike AI QC Evaluation:
  • Human QC Annotation is performed manually by a linguist during review.
This workflow allows organizations to:
  • audit AI quality,
  • identify recurring issues,
  • benchmark linguistic weaknesses,
  • and improve future localization workflows.

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When Human QC Annotation Happens

Human QC Annotation occurs: 
AI generates subtitle Order
        ↓
Order assigned to linguist/editor
        ↓
Linguist reviews segments
        ↓
Annotations added where needed
        ↓
Order delivered
        ↓
Annotation Summary generated
This workflow is available only when:
  • Human QC Annotation is enabled in configuration settings.
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Important Operational Behavior

Linguists do not need to annotate every subtitle segment.
Annotations are only added:
  • to segments where issues are identified.
This keeps the workflow:
  • efficient,
  • scalable,
  • and operationally practical.
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Human QC Categories

Editors can tag subtitle segments using predefined categories:

Accuracy

Used when translated meaning is incorrect or incomplete.

Terminology

Used when approved terminology or glossary usage is inconsistent.

Hallucination

Used when AI introduces fabricated, missing, or unsupported content.

Verity

Used when factual correctness or contextual truthfulness is affected.

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Severity Levels

Each annotation can additionally include:
  • severity classification.
Available severity levels include:

Minor

Small issue with limited localization impact.

Major

Significant issue affecting localization quality or readability.

Critical

Severe issue requiring immediate correction.

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Example Annotation Workflow

Example subtitle segment: 
Source:
"We launched the feature globally."

AI Translation:
"We launched the bug globally."
Human QC Annotation: 
Category: Accuracy
Severity: Major
Issue:
Incorrect translation altered intended meaning.

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Annotation Summary

Once the linguist delivers the Order: Project Management Users can access:
  • Human QC Annotation results.
The platform generates an annotation summary including:
  • number of annotated segments,
  • category distribution,
  • severity distribution,
  • top recurring issues,
  • and localization quality insights.
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Example Annotation Summary

Human QC Annotation Summary

Segments Reviewed: 245
Annotated Segments: 18

Category Distribution:
- Accuracy: 8
- Terminology: 5
- Hallucination: 3
- Verity: 2

Severity Distribution:
- Minor: 10
- Major: 6
- Critical: 2

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Exporting Annotation Reports

Human QC Annotation reports can be downloaded as:
  • Excel (.xlsx)
This enables:
  • enterprise auditing,
  • vendor benchmarking,
  • linguist performance reviews,
  • and multilingual quality reporting.

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AI QC vs Human QC Annotation

AI QC Evaluation

Automated evaluation using configurable prompts, models, and quality criteria.

Human QC Annotation

Manual linguist-driven quality tagging performed during subtitle review.
Organizations commonly combine both workflows to benchmark AI quality while also collecting human linguistic feedback.

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Important Operational Notes

Yes. AI-only Orders remain editable, rerunnable, and assignable to the inner team members after generation.
Yes. Orders may be assigned internally or externally depending on operational workflows.
Yes. Organizations may onboard their own editors, linguists, agencies, or dubbing studios.
Yes. Human review support can also be coordinated through Ollang-managed linguists.
No. Editors only see explicitly assigned Orders.
Yes. Orders may be rerun after workflow modifications, translation changes, or dubbing refinements.