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What is rawctx?

Rawctx functions as a specialized AI evidence layer aimed at teams creating customer-oriented AI assistants, copilots, and agents. It carefully records each response alongside officially sanctioned meanings, contextual references, metadata from model executions, trace identifiers, histories of corrections, and exportable proof bundles. This robust feature allows teams to analyze the reasoning behind every AI-generated response, detailing the evidence and business definitions employed, any alterations made after review, and the current trust proof status, whether it is confirmed, awaiting verification, or solely local. Moreover, rawctx offers functionalities for maintaining comprehensive answer audit logs, enabling exports in formats such as JSON, CSV, or proof, consolidating source reference evidence, and establishing verification processes that may be either public or private, addressing essential sectors like support, sales, finance, legal, and operations. In addition to these features, rawctx fosters a culture of accountability, empowering organizations to enhance transparency in their AI engagements while ensuring rigorous oversight of AI interactions. Ultimately, rawctx serves as a vital tool that reinforces trust in AI-driven communications.

What is LangSmith?

In software development, unforeseen results frequently arise, and having complete visibility into the entire call sequence allows developers to accurately identify the sources of errors and anomalies in real-time. By leveraging unit testing, software engineering plays a crucial role in delivering efficient solutions that are ready for production. Tailored specifically for large language model (LLM) applications, LangSmith provides similar functionalities, allowing users to swiftly create test datasets, run their applications, and assess the outcomes without leaving the platform. This tool is designed to deliver vital observability for critical applications with minimal coding requirements. LangSmith aims to empower developers by simplifying the complexities associated with LLMs, and our mission extends beyond merely providing tools; we strive to foster dependable best practices for developers. As you build and deploy LLM applications, you can rely on comprehensive usage statistics that encompass feedback collection, trace filtering, performance measurement, dataset curation, chain efficiency comparisons, AI-assisted evaluations, and adherence to industry-leading practices, all aimed at refining your development workflow. This all-encompassing strategy ensures that developers are fully prepared to tackle the challenges presented by LLM integrations while continuously improving their processes. With LangSmith, you can enhance your development experience and achieve greater success in your projects.

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Integrations Supported

AgentForge
Azure Marketplace
Disco.dev
LangChain
LangGraph
Noma
Python
TierZero
Voker
ZenML

Integrations Supported

AgentForge
Azure Marketplace
Disco.dev
LangChain
LangGraph
Noma
Python
TierZero
Voker
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

$9.99/1000logs
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

rawctx

Date Founded

2026

Company Location

South Korea

Company Website

hub.rawctx.dev

Company Facts

Organization Name

LangChain

Company Location

United States

Company Website

www.langchain.com/langsmith

Categories and Features

Categories and Features

Software Testing

Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing

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