Inferable
Inferable is an open-source developer platform that enables the creation of reliable, secure AI agents by converting existing internal APIs, functions, and scripts into conversational AI automations with a ReAct-like agent strategy.
https://www.inferable.ai?ref=aipure
Product Information
Updated:Feb 16, 2025
Inferable Monthly Traffic Trends
Inferable achieved 30,249 visits with a 2077.8% growth in January 2025. The significant increase in traffic is likely driven by the growing trend of generative AI in marketing and the product's unique features, such as distributed tool calling architecture and on-premise execution, which enhance security and flexibility. Additionally, the White House's order to remove barriers to American AI innovation may have boosted interest in AI applications like Inferable.
What is Inferable
Inferable is a managed developer platform designed to simplify the building of LLM-based applications and AI automations. It provides a framework for developers to transform their existing codebase, internal systems, and APIs into intelligent agents that can be interacted with through conversation via Slack, email, or programmatic APIs. The platform supports multiple programming languages including Node.js, Golang, and .NET, with more languages planned for the future.
Key Features of Inferable
Inferable is an open-source platform that enables developers to create AI agents by integrating with existing codebases, APIs, and data. It features a distributed message queue system, supports multiple programming languages (Node.js, Golang, C#), and provides built-in ReAct agents for complex problem-solving. The platform offers enterprise-grade security, observability, and human-in-the-loop capabilities while allowing functions to run on local infrastructure.
SDK Language Support: First-class support for Node.js, Golang, and C# with more languages planned, allowing developers to integrate AI capabilities using their preferred programming language
Distributed Function Orchestration: Built on a distributed message queue with at-least-once delivery guarantees, ensuring reliable and scalable AI automation execution
Human-in-the-Loop Integration: Allows pausing function execution for human intervention and seamlessly resumes when input is received, regardless of time delay
Secure On-premise Execution: Functions run on local infrastructure with long-polling for instructions, eliminating the need for incoming connections and maintaining data privacy
Use Cases of Inferable
Internal Tooling Consolidation: Combine fragmented internal systems, codebases, and scripts into unified conversational agents accessible through Slack or email
Database Operations: Create text-to-SQL agents that can interact with databases (read-only or read/write) through natural language commands
API Integration: Deploy containers to interface with REST/GraphQL APIs, enabling AI agents to interact with existing services through natural language
Support Automation: Build AI agents that can handle tier-2 support requests by accessing internal documentation and systems
Pros
Open-source and self-hostable for complete control over data and compute
No new frameworks to learn - works with existing code through decorators
Enterprise-ready with built-in security and observability features
Cons
Limited language support currently (only Node.js, Golang, and C#)
Still in beta for some SDK implementations
Requires technical expertise for implementation and maintenance
How to Use Inferable
Create an Inferable Account: Go to Inferable Cloud (inferable.ai) to create your free cluster. A cluster is a logical grouping of functions and agents that work together.
Choose SDK & Install: Select and install the appropriate SDK for your programming language. Inferable supports NodeJS (GA), Golang (Beta), and .NET (Beta). Install using your language's package manager.
Initialize Inferable: Create an initialization file (e.g., i.ts for TypeScript) to set up Inferable in your project. Configure your API key and basic settings.
Register Functions: Decorate your existing functions using the Inferable SDK to make them available to the AI agent. Include function name, description, and input schema using the provided schema definition tools.
Start Local Service: Run your application with the registered functions. This will start a local server that establishes an outbound connection to Inferable's control plane.
Create AI Agent: Use the Inferable platform to create an AI agent that can access your registered functions. The agent will use a ReAct-like strategy to reason about tasks and execute functions.
Test Integration: Create a test run with a simple prompt (e.g., 'Say hello to John') to verify the agent can properly access and execute your registered functions.
Monitor & Observe: Use the Inferable Playground and API to monitor the health of your SDKs, runs, and function executions. Review logs and performance metrics through the provided observability tools.
Implement Error Handling: Configure retry policies and timeout settings for your functions to handle potential failures and ensure reliable execution of your AI workflows.
Deploy to Production: Once testing is complete, deploy your Inferable-enabled application to production. The functions will continue to run in your own infrastructure while maintaining secure communication with Inferable's control plane.
Inferable FAQs
Inferable is an open-source platform for creating AI agents that can integrate with existing codebases, APIs, and data. It allows you to turn internal APIs and tools into conversational AI agents.
Official Posts
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Analytics of Inferable Website
Inferable Traffic & Rankings
30.2K
Monthly Visits
#985300
Global Rank
-
Category Rank
Traffic Trends: Nov 2024-Jan 2025
Inferable User Insights
00:03:59
Avg. Visit Duration
2.24
Pages Per Visit
55.42%
User Bounce Rate
Top Regions of Inferable
US: 65.97%
IN: 26.33%
PL: 7.71%
Others: NAN%
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