Scaled Cognition

About Scaled Cognition

Launched Mar 03, 2025

Description

Solving agentic artificial intelligence

Scaled Cognition has created the world's first Agentic Pretrained Transformer (APT) that optimizes actions, resulting in a new state-of-the-art for agentic workflows. The system is pretrained on large-scale simulated interactions, which involve taking actions across complex APIs and domains while adhering to instructions and policies, enforces deterministic constraints and anti-hallucination rules when calling functions, and has a built-in API simulation to test against mock APIs without hooking up backends.

Scaled Cognition Key Features

Automate workflows
Resolve CX interactions at a fraction of the cost
Integrates with existing support platforms
Personal data never leaves your enterprise
Stateless system retains no data
One system backs all voice, chat, email applications
Multi-lingual
Hosted or VPC/On-Premise deployment options
Low inference time cost

Scaled Cognition Use Cases

Targeted at conversational AI applications like CX, with plans to expand to other verticals in the future
Varied applications in Telecom, Travel, Insurance, Utilities, Shipping/ Logistics, Retail/E-Commerce, Information Technology, Finance, Healthcare

Pros

Innovative approach to agentic artificial intelligence using Agentic Pretrained Transformer (APT).
Optimizes actions for agentic workflows, potentially increasing efficiency.
Pretrained on large-scale simulated interactions, providing a robust training environment.
Adherence to instructions and policies with deterministic constraints and anti-hallucination rules ensures accuracy and reliability.
Built-in API simulation allows for testing against mock APIs without backend integration, enhancing development flexibility.
High potential for application across various complex APIs and domains.

Cons

Complexity of implementation may pose challenges for new users or developers without significant experience.
Potential lack of real-world testing data as it relies heavily on simulated environments.
The advanced nature of the app may result in a steep learning curve.
Dependence on accurate implementation of instructions and policies to ensure optimal performance.