Document Q&A 05 Apr 2023
Training, interacting, debugging, monitoring platform.

Generated by ChatGPT

Proc is a Generative AI platform that aims to streamline AI development for creators, developers, and teams. It offers a range of tools and functionalities to develop, deploy, and observe AI in production.

With Proc, users can build, compare, and ship AI applications in a single place, utilizing a variety of collaborative low to no-code tools.The platform provides several core pillars for AI development: Memory, Interface, and Dashboard.

These pillars encompass sub-components that work together for a holistic solution designed for collaboration. Proc adopts standards like Opentelemetry and Prometheus and utilizes readily available open-source models such as META's LLAMA 2 to reduce the learning and integration curve.Some of the specific tools available in Proc include an AI Trainer, a chat interface for interacting with AI, a logs debugger for debugging AI models, performance tracing to monitor AI performance, and an API for integration with existing systems.

The AI Trainer allows users to ingest and index data without code to train AI models. The chat interface enables user-friendly interaction with AI, while the logs debugger offers a flow-based tool for AI model debugging.

Performance tracing, based on Opentelemetry, helps monitor AI performance, and the API allows easy integration with existing systems.Proc places emphasis on giving control to users and aims to provide extensible and programmable access for workflow creation, deployment, and monitoring.

The platform is designed for full automation and deployment confidence, with a goal of making artifacts exportable to other platforms and systems.Please note that the tool is in a private beta phase and offers an upgrade for existing OpenAI integration.

Save was manually vetted by our editorial team and was first featured on September 2nd 2023.
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Pros and Cons


Deployment and observation
Variety of tools
Collaborative low-no code tools
Adopts Opentelemetry and Prometheus
Utilizes META's LLAMA 2
Chat interface
Logs debugger
Performance tracing
Integration API
Emphasizes user control
Extensible and programmable access
Full automation and deployment
Exportable artifacts
Private beta phase
Memory, Interface, Dashboard pillars
Interaction user-friendly
Flow-based debugging
Opentelemetry-based performance monitoring
Exports to other platforms
Single place for all apps
Reduces learning, integration curve
Control given to users
Model swap feature
Integrated metrics
Full observability
Prometheus metrics endpoint
Ease and confidence in deployment
Cloud or Hardware hosting
Processing of sensitive data
Custom integrations
Semantic Knowledge Base
Product Copilots
Sales Copilots
Customer Support
Personalised Content Generation
Trend Detection rules
Expert System
Robust developer support
Built for collaboration
Share and embed capacity


Private beta phase
Relies on OpenTelemetry
Dependent on META's LLAMA 2
Complex platform with multiple components
Unclear how to switch models
No details on pricing
Mention of setup confusion
Lack of concrete success stories
No specific information on integrations


What is Proc?
What are the functionalities that Proc provides?
What is the aim of Proc?
What are the core pillars of Proc?
Can I integrate Proc with existing systems?
How does the Trainer tool in Proc function?
Can I interact with AI using Proc?
What's the debugging tool provided by Proc?
How does Proc assist with AI performance monitoring?
Is there a code-free data indexing feature in Proc?
How does Proc support collaboration?
What does Proc mean by 'control to users'?
Are there any extensible features in Proc?
Can artifacts from Proc be exported to other platforms?
Is Proc designed for full automation?
What open-source models does Proc utilize?
How does Proc help with deployment confidence?
What is the status of Proc, is it available for use?
Does Proc offer an upgrade for existing OpenAI integration?
What's the purpose of the AI chat interface in Proc?

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