Accuracy Booster

The Teneo Linguistic Modeling Language (TLML) boosts accuracy of LLM and NLU

Unlock Customer Experience Analytics

The Teneo Linguistic Modeling Language (TLML) is a sophisticated, deterministic language understanding system that identifies and interprets word patterns in a caller's speech.

TLML adds an additional deterministic layer on top of NLU, LLM and machine-learning classification, enabling high precision unachievable with probabilistic models.

Designed to produce matches that trigger specific actions based on the caller's intent, TLML power-up OpenQuestion to accurately interpret spoken language and enhance contact center operations.

Accuracy Booster
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How does TLML work?

OpenQuestion greets callers automatically with "How can I help?". Harnessing the power of TLML, OpenQuestion identifies a caller's response, assigns an intent to the call, and extracts relevant information from the text to determine the most suitable course of action.

For example, without Teneo, a match on "unlock" would simply process the request and drop the call into an account support queue or require the creation of a whole new intent and workflow to probabilistically respond to clarifications like "my device is locked", "password is wrong", or "login says my account is locked".

With Teneo, the system matches on "unlock" and then asks for clarification to accurately match the language on "device is locked", "password is wrong", or "login says locked", subsequently routing the call properly.

This approach employs a single flow, unified clarification, and simple language constraints to ensure proper routing.

What sets OpenQuestion Apart? 

OpenQuestion sets itself apart by leveraging the TLML system to comprehend and interpret spoken language with greater precision than conventional techniques.

It utilizes a cohesive workflow that relies on words and context for determining conditions, rather than manually constructed rulesets.

As a result, TLML simplifies bot and dialogue management by standardizing deployments and minimizing the reliance on ad hoc solutions and human intervention.

Other platforms often depend on metadata markup or custom scripts, necessitating the use of static and ever-expanding rulesets. This approach leads to an increased demand for resources, additional infrastructure and personnel dedicated to maintenance and support.

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Key Benefits of TLML

Accuracy booster for LLMs, NLU and ML
TLML on top of ML is the mechanism that allows you increase the accuracy. Improve your accuracy rate from 80% to 95%

Guardrails for Generative AI and Precision
Implement safety measures at scale to ensure accuracy and relevance of AI-generated content as well as ensure correct interpretation of close-lying intents.

High-Functioning and Critical Component
Designed to optimize and scale performance across all aspects of bot and dialogue management.


By combining TLML with other AI-based technologies, OpenQuestion enhances agent and customer engagement and accelerates competency.

The advanced language understanding capabilities of TLML enable more accurate and efficient handling of customer calls, making it an essential asset for any contact center.

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OpenQuestion in 2 Minutes