CallTech Inc.

AI-driven Call Center Intelligence for Regulated, High-Volume Operations

Employees: 5 employees
Founded: Founded 2024
Locations: 1 location

CallTech Inc.

AI-driven Call Center Intelligence for Regulated, High-Volume Operations

Employees: 5 employees
Founded: Founded 2024
Locations: 1 location

About

CallTech Inc. was founded in June 2024 and is based in İzmir Technology Development Zone (İzmir Bilişim Vadisi). The company is a spin-off of AdresGezgini Inc., a technology company operating since 2007.

The founding team of CallTech consists of three PhD-level Electrical and Electronics Engineers, who are also the founders of AdresGezgini Inc. and have extensive experience in applied AI, speech analytics, and large-scale call center systems. AdresGezgini Inc. has been officially recognized as an R&D Center since 2018 and has executed multiple TÜBİTAK TEYDEB-funded R&D projects in the field of speech and conversational analytics.

While CallTech Inc. itself is a relatively young company, the underlying technology and domain expertise are the result of more than six years of continuous R&D experience in speech analytics and conversational AI, originating from four interconnected TÜBİTAK TEYDEB projects conducted within AdresGezgini Inc.

The platform processes high-volume voice data, handling thousands of calls per month and several hundred hours of audio recordings, enabling continuous monitoring of call quality, conversational anomalies, and agent performance. These volumes provide a realistic enterprise-like operational baseline for validating scalability, performance, and analytical accuracy.

Services

AI-Powered Speech & Conversation Analytics

A multi-modal speech analytics service that processes recorded voice interactions to extract structured conversational insights. The system performs acoustic segmentation using signal processing and convolutional neural networks (CNNs), distinguishing speech, silence, and overlap segments. Conversations are transcribed using transformer-based speech-to-text models and structured as bi-directional dialogue logs between customer and agent. The service generates actionable metrics such as talk-tim

LLM-Based Sentiment & Interaction Intelligence

A context-aware conversational intelligence service that applies large language models (LLMs) to transcribed call data for sentiment analysis and interaction evaluation. The system independently evaluates customer and agent emotional dynamics, detecting dissatisfaction trends, escalation risk, and compliance-sensitive interaction patterns. The architecture supports multi-layer analysis, combining text-based LLM reasoning with statistical interaction features to identify anomalous or high-risk c

Anomaly Detection & Performance-Based Call Routing Intelligence

A data-driven anomaly detection and operational optimization service designed to improve call center performance at scale. The platform combines configurable rule-based logic (e.g., keyword presence/absence, domain-specific triggers) with machine learning–based classification models to detect statistically abnormal interaction patterns. Over time, historical interaction data is used to generate performance profiles for customer service agents and behavioral patterns for recurring customers. The