skopıa

The command center of digital intelligence

The detection of driver errors through AI-powered early predictions, the prevention of accidents by generating timely warnings, and the 24/7 monitoring and supervision of vehicles engaged in intercity freight or passenger transportation, with the aim of preventing accidents.

From Noise to Intelligence framework
Simultaneous Filtering:

Millions of raw data instantly through strategic filters.

Smart Tagging:

content on the basis of sector, intention and emotion Automatically classifies

Contextual Attribution:

Logical chunks of data Combines into a network

Wide-Ranging Monitoring:

From social media cascades Full command of visual analysis.

BEYOND TEXT IMAGE ANALYSIS

FACE RECOGNITION

Seconds of searched people in live broadcasts Detection with sensitivity

VLM & OCR

Textual depiction of image frames and Reading the texts on the screen

OBJECT DETECTION

Such as a vehicle, ammunition, or logo in the media Automatic detection of objects

MULTILINGUAL STT

80% accuracy rate in Kurdish dialects (Soranil Kurmanji)

News and live stream analysis

Public domain news sites and live streaming merge in the same enrichment pipeline as social media
data.

STT Technology

Second-accurate text translation and instant word alarms

Semantic Clustering

It collects the same news described with different words in a single title.

24/7 Live Monitoring

Uninterrupted operation in TV, radio and internet broadcasts

1. Sources
Social
News
AV
2. Buffer (Kafka / DLQ)
Buffer (Kafka / DLQ)
Best Effort principle. A single failure does not stop the system.
3. Enrichment (NLP / STT / Translation)
Enrichment (NLP / STT / Translation)
Isolated Pools
1. Persistent Storage
2. Time Series
3. Full Text
4. Graph (SNA)
5. NLP Tags
6. Media Archive
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REST API & Analyst Panel
The Cognitive Core: AI Content X-Ray

The Turkish-first, context-aware NLP engine makes ~200 classifications per second and separates the raw text into 5 different structured intelligence tags.

Sector & Sub-Sector
Finance ➔ Banking Detail: 16 Main Sectors, 76 Sub-Sectors, Context-aware structure.
Intent
Complaint
"The system crashed again! @BankName I haven't been able to make a transaction for 3 hours, no idea where my money is. Disgrace! 😡"
Sentiment (Polarity)
Negative
Emotion
Anger (Ekman’s 6 basic emotion model)
Social Network Analysis (SNA): Influence and Faction Mapping
Interactions are modeled as a directed network. The analytical engine deciphers opinion leaders, hidden administrators, and echo chambers within the network.
Centrality: Influence (PageRank). Overall influence power in the network. High In-Degree actors. Bridge (Betweenness): Bottleneck actors controlling information flow between disconnected communities. Community (Echo Chamber): Closed to the outside, factions interacting internally. Shadow leaders are inside this cluster.

RECTOR DETERMINATION

Precise classification in 16 main sectors and 76 sub-sectors

INTENT ANALYSIS

Determination of intentions such as
complaints, requests or information

Emotion

6 basic emotion models such as anger, fear, admiration

POLARİTE

Measurement
of whether content is negative, positive, or neutral.