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Langdock

Empower employees with AI, control your data

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June 16, 2023

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Langdock

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Empower employees with AI, control your data

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Overview Discussion

Overview

Langdock is an AI platform designed to increase productivity within teams. It acts as a daily GDPR-compliant chat companion for employees, providing a unified platform for automations and custom assistants.

Langdock hosts locally learnt models (LLMs) which allows companies to maintain full control over their data. Notably, it supports GDPR-compliant servers in Europe, including third-party AI models such as the GPT-4 model, hosted by Microsoft Azure in Stockholm.On this platform, companies can automate tasks, generate insights through AI interactions and collaborate more efficiently.

Langdock's features include AI chat for daily use, AI assistants for teams, the ability to automate workflows with AI, and an integration function that connects various tools and apps.

The platform can be accessed via API, providing broad flexibility and scalability.Data security is a significant aspect of the platform, with AES-256 encryption for data at rest and in transit, and robust processes to ensure workspace privacy and information accuracy.

It offers custom data retention and audit logs, and inputs aren't used for re-training models, ensuring data privacy.Furthermore, the platform's ISO 27001 and SOC 2 Type 2 certifications demonstrate adherence to strict security measures and data integrity.Langdock is also customizable, with users being able to connect their tools, choose their model and location, and access the API.

Additional features include a built-in prompt library, multi-user collaboration capabilities, and the ability to train and prepare the workforce for the era of AI.

Equipped with these tools and features, Langdock empowers employees to handle everyday tasks more effectively.

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May 11, 2023

Initial release of Langdock.

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Pros and Cons

Pros

Creating LLM plugins

Testing LLM plugins

Deploying LLM plugins

Monitoring LLM plugins

API to LLM conversion

Supports ChatGPT and LangChain

Future Bing and HuggingFace support

Request logging and monitoring

Real-time monitoring of plugin usage

Customisation of dashboards

Tracking funnels and aggregated metrics

Support for enterprise-grade security

Compliance features

Permissioning features

Free version with usage limits

Pay-per-use model

Open source availability

Designed for team productivity

Hosts locally learnt models

GDPR-compliant servers in Europe

Task automation

Facilitates efficient collaboration

API access

AES-256 encryption for data

Robust workspace privacy

ISO 27001 and SOC 2 Type 2

Custom data retention

Audit logs

Inputs not used for re-training

Built-in prompt library

Multi-user collaboration

Workflow automation features

Integration function connects tools and apps

Customizable platform

Supports Microsoft Azure hosting

Extensive documentation and tutorials

Product support via Discord and live chat

GDPR-compliant data privacy

Data segregated by workspace and organisation

Sensitive information redaction

Highly customizable features

Single API for all models

Broad flexibility and scalability

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Cons

No Bing support yet

No HuggingFace support yet

Limited to LLM plugins

No training data for LLMs

Limited free usage

Open source in future only

GDPR compliance restricts data usage

Limited models available

Specifically designed for productivity teams

Enterprise features require premium

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Q&A

What is the purpose of Langdock?

Langdock serves as an AI platform designed to augment team productivity. It functions as a daily GDPR-compliant chat companion aiding employees while maintaining full control over data by using locally learnt models (LLMs). Powered by automation and AI assistants, Langdock provides a unified platform for workflows, enabling efficient team collaboration and business insights generation.

How does Langdock make integration of AI models into apps easier?

Langdock simplifies AI model integration into applications by allowing users to convert any API into an LLM plugin. This is achieved by importing or manually adding API documentation. What this means is users can effortlessly integrate AI models into any application that supports LLM plugins.

What is the specialty of LLM plugins in Langdock?

The LLM plugins in Langdock are built to allow users to integrate AI models into their own applications seamlessly. Thanks to an all-in-one product suite that includes creation, testing, deployment, and monitoring of these plugins, Langdock becomes a comprehensive tool for integrating AI into applications.

What are some of the AI models that Langdock supports?

Langdock has native support for ChatGPT and LangChain. It plans to roll out support for other AI models such as Bing, HuggingFace and others in the future. This range of support makes Langdock a versatile platform for integrating different AI models.

How does Langdock platform help in real-time monitoring of plugin usage?

Langdock platform incorporates detailed request logging and real-time monitoring to help developers track plugin usage instantaneously. Key metrics such as latencies and errors can be tracked. Users can further configure their dashboards and track funnels and aggregated metrics, providing them vital business insights.

What meant by usage limits in Langdock's free version?

Usage limits in Langdock's free version imply that users can use the platform without cost up to certain predefined limits. Beyond these limits, users are required to pay per use to gain unrestricted access to all features.

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When will Langdock be releasing its platform as open source?

Langdock plans on releasing its platform as open source in June 2023. This means users will have the ability to inspect and run Langdock's core functionality independently for their projects.

How does Langdock ensure GDPR-compliance?

Langdock guarantees GDPR-compliance by hosting all services on GDPR-compliant servers located in the European region. Information entered into Langdock is not used to re-train models, further ensuring data privacy. Moreover, Langdock supports GDPR-compliant organizations such as Microsoft Azure.

What role does Microsoft Azure play in Langdock?

Microsoft Azure plays a vital role in hosting Langdock's third-party AI models on GDPR-compliant servers in Europe. For example, the GPT-4 model is hosted by Microsoft Azure located in Stockholm.

How can Langdock help automate tasks and generate insights?

Langdock helps in automating tasks and generating insights through AI interactions. It allows companies to deploy AI chats for daily use, AI assistants for teams, and facilitates automation of workflows using AI. This leads to a collaborative and efficient working environment, generating valuable insights for the business.

What security measures are in place to ensure data security on Langdock?

Langdock deploys stringent security measures for data protection. It employs AES-256 encryption for data at rest and in transit. Robust processes are in place to safeguard workspace privacy and ensure the accuracy of information. Features like custom data retention and audit logs further strengthen the security framework.

What certifications does Langdock have to guarantee data integrity?

Langdock prides itself on ISO 27001 and SOC 2 Type 2 certifications. These certifications not only attest to Langdock's compliance with strict data security processes but also ensure the integrity of customer data and continuous service.

How customizable is the Langdock platform?

Langdock platform is highly customizable. Users can choose from models hosted in Europe and the United States, connect all their tools and apps, and access the platform via a unified API. This offers users the flexibility and scalability required to tailor the platform as per their needs.

What are some of Langdock's features for team collaboration?

For team collaboration, Langdock provides features like AI chat for daily use, AI assistants specifically designed for teams and the ability to automate workflows with AI. Furthermore, users can save prompts in their library and share them with their team. These features foster efficient and seamless team collaboration.

How does Langdock platform support training for the AI era?

Langdock supports training for the AI era through its commitment to providing high-quality courses that prepare the workforce for the advancements in AI. This educational feature is aimed at making the workforce competent in dealing with AI-powered solutions.

What are the pricing options for Langdock?

Langdock offers flexible pricing options. Users can use the platform for free with usage limits or pay per use to gain unrestricted access to all features. Additionally, there are dedicated support, additional features, customized pricing plans for enterprise customers.

What is the significance of ISO 27001 and SOC 2 Type 2 certifications for Langdock?

ISO 27001 and SOC 2 Type 2 certifications for Langdock demonstrate the platform's adherence to rigorous data security processes. These certifications not only ensure the integrity of customer data but also guarantee service continuity, thereby proving Langdock's secure handling of user data.

How does Langdock ensure data segregation and workspace privacy?

Data segregation in Langdock is achieved through the implementation of row-level access mechanisms, which separate data by workspace and organization. The platform also has robust processes to ensure workspace privacy and maintaining information in an accurate manner.

How does Langdock protect data at rest and in transit?

Langdock employs AES-256 encryption to safeguard data at rest. All data in transit is encrypted with TLS 1.3 using AES-256. These mechanisms ensure the secure transmission and storage of data, thereby protecting sensitive information from unauthorized access.

What additional functionalities does the API access in Langdock offer?

API access in Langdock offers users additional functionalities such as the flexibility to connect all their tools and apps to the platform, choose from models hosted in various locations, and the ability to use one API for all models and features. This broadens the usability and scalability of the platform.

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