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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 Analytics section inside the Ollang Project Management Dashboard helps organizations:
  • monitor localization performance,
  • evaluate multilingual quality,
  • understand credit consumption,
  • track operational delivery,
  • benchmark AI performance,
  • and analyze human review behavior.
Analytics provide visibility into:
  • Order performance,
  • AI localization quality,
  • Human review behavior,
  • QC progression,
  • operational delivery,
  • and billing-related insights.

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Analytics Visibility and Permissions

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Access Requirements

Analytics visibility requires:
  • Access Billing permission.
Only Project Management Users with Access Billing permissions can view:
  • Analytics,
  • Payment Overview,
  • Credit Overview,
  • QC performance,
  • and financial reporting.
Standard Project Management Users without Access Billing permission cannot access the Analytics section.

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Analytics Sections

The Analytics dashboard currently includes:

Order Analytics

Analyze localization activity across Orders.

Payment Overview

View invoicing and outstanding payment information.

Credit Overview

Monitor AI credit availability and usage.

Recent Order Details

Review recently processed localization Orders.

QC Score Progression by LLM

Understand localization quality progression over time.

Average Human Edit Percentage

Understand how much AI-generated output required human modification.

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Order Analytics

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Overview

Order Analytics helps organizations understand:
  • localization volume,
  • workflow activity,
  • delivery performance,
  • language pair trends,
  • and operational behavior.
Organizations can analyze localization activity across:
  • Order types,
  • language pairs,
  • delivery priorities,
  • and time periods.

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Order Analytics Filters

Order Analytics supports the following filters:

Start Date / End Date

Analyze operational performance within a selected timeframe.

Order Type

Filter analytics by localization workflow type.

Source Language

Analyze localization performance from a selected source language.

Target Language

Analyze localization behavior for specific target markets.

Order Level

Analyze AI-only or AI + Human Review workflows.

Delivery Type

Filter between standard and rush delivery workflows.

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Example Analytics Query

Example: 
Filters Applied:

Start Date:
January 1

End Date:
February 28

Source Language:
English

Target Language:
French

Order Type:
Subtitle Translation
Result: 
Localized subtitle activity
for English → French
within the selected timeframe
D1

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Credit Overview

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Overview

Credit Overview provides visibility into:
  • total AI credits,
  • remaining AI credits,
  • and localization consumption.
This helps organizations:
  • manage localization budgets,
  • understand operational usage,
  • and monitor available processing capacity.

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Credit Visibility

The dashboard currently displays: 
Total AI Credits
This helps operational teams understand:
  • available localization capacity,
  • and current AI usage availability.

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Payment Overview

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Overview

Payment Overview provides billing-related visibility for operational teams. This section helps organizations understand:
  • invoice-related activity,
  • pending payment behavior,
  • and financial status.

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Payment Information

The Payment Overview currently includes:

To Be Invoiced

Pending operational amounts expected to be invoiced.

Outstanding Balance

Existing balance pending payment resolution.
D3

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Recent Order Details

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Overview

Recent Order Details provide operational visibility into:
  • recently processed Orders,
  • localization activity,
  • and workflow execution.
This helps Project Management Users:
  • quickly monitor activity,
  • identify recent deliveries,
  • and review localization progress.
D4

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Typical Order Details

Recent Orders commonly include:
  • Order information,
  • localization workflow details,
  • language pair information,
  • status,
  • and operational delivery details.

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Advanced Search Navigation

The Analytics section includes:
  • Advanced Search
This action redirects users to:
  • the Global Search page.
This enables teams to:
  • deeply investigate Orders,
  • search historical activity,
  • and perform operational tracking.
Workflow: 
Analytics
        ↓
Advanced Search
        ↓
Global Search Page

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QC Score Progression by LLM

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Overview

QC Score Progression by LLM provides:
  • aggregated localization quality trends.
Rather than comparing individual provider runs directly, this analytics view helps organizations understand: 
How localization quality
improves or changes over time
for a selected workflow.

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Available Filters

QC Score Progression supports:

Start Date / End Date

Analyze localization quality across a selected timeframe.

Source Language

Filter by source language.

Target Language

Filter by target language.

Order Type

Analyze QC progression for a specific workflow.

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How QC Progression Works

The system analyzes:
  • average QC scores,
  • quality progression trends,
  • and localization improvements.
Example: 
English → French
Subtitle Translation
Last 2 Months
The dashboard may show: 
First Average QC Score:
78%

Latest Average QC Score:
92%

Best Performing LLM:
Provider X

Improvement:
+14%
This helps organizations understand:
  • quality evolution,
  • workflow effectiveness,
  • and localization performance over time.

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Important Clarification

QC Score Progression is an aggregated trend analysis and not a side-by-side comparison of every provider run.
The platform highlights:
  • first QC score average,
  • latest QC score average,
  • best-performing LLM,
  • and quality improvement trends.
D5

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Average Human Edit Percentage

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Overview

Average Human Edit Percentage helps organizations understand: 
How much AI-generated content
was modified during human review.
This metric is especially useful for:
  • benchmarking provider quality,
  • evaluating localization efficiency,
  • identifying problematic language pairs,
  • and optimizing workflows.

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Human Edit Filters

Average Human Edit Percentage supports:

Start Date / End Date

Analyze human edit behavior within a selected timeframe.

Source Language

Analyze edit behavior for specific source languages.

Target Language

Analyze edit behavior for target markets.

Order Type

Evaluate edit percentage across localization workflows.

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Measurement Methodology

Human Edit Percentage is measured at:
  • segment level.
This means the platform evaluates: 
How much subtitle content
required modification
during human review.
The dashboard provides:
  • overall average human edit percentage,
  • and Order-level edit details.

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Example Human Edit Analysis

Example: 
English → French
Subtitle Translation
Date Range:
30 Days
Result: 
Average Human Edit:
22%

Order Details:
Order A → 15%
Order B → 32%
Order C → 18%
This helps organizations identify:
  • efficient workflows,
  • high-performing providers,
  • and problematic localization patterns.
D6

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Using Analytics for Workflow Optimization

Organizations commonly use Analytics to answer questions such as: 
Which workflow performs best
for English → French subtitles?

Which provider reduces
human editing effort?

Which localization workflows
improve QC score over time?
This helps teams:
  • improve localization quality,
  • optimize provider selection,
  • reduce review effort,
  • and benchmark multilingual performance.

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Best Practices

Organizations typically achieve the best outcomes by combining: 
QC Score Progression
        +
Human Edit Percentage
        +
AI QC Evaluation
        +
Human QC Annotation
This provides visibility into:
  • AI quality,
  • human correction effort,
  • localization consistency,
  • and long-term optimization opportunities.

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Important Operational Notes

Only users with Access Billing permission can access the Analytics section.
No. The analytics show aggregated quality progression and best-performing LLM insights rather than run-by-run comparisons.
It measures how much AI-generated content was modified during human review at segment level.
Yes. Analytics support Source Language and Target Language filtering.
Advanced Search redirects users to the Global Search page for deeper operational investigation.
Yes. Analytics help organizations benchmark localization quality, provider effectiveness, and human review effort.