AutoGen Services

Multi‑agent LLM collaboration, automated tools, and human‑in‑the‑loop

Build Scalable Multi-Agent AI Systems with Microsoft AutoGen

Microsoft AutoGen enables collaborative AI agents that plan, reason, execute, critique, and iterate together to solve complex business and engineering problems. At Oodles, we design and deploy AutoGen-powered systems using Python as the core language, combined with JavaScript-based interfaces, LLMs, tool APIs, and containerized infrastructure to deliver reliable, observable, and production-ready multi-agent solutions.

What is AutoGen?

AutoGen is a Microsoft-developed, open-source framework written in Python for building multi-agent conversational AI systems. It enables multiple specialized agents to collaborate through structured conversations, shared memory, and tool usage.

AutoGen supports integration with modern LLMs, external APIs, databases, and custom business logic, making it ideal for enterprise-grade, human-in-the-loop AI workflows.

Why Choose Oodles for AutoGen Services?

✓ Architecture-first AutoGen system design
✓ Human-in-the-loop safety and approvals
✓ Deep observability, logging, and evaluation
✓ Multi-model and multi-vendor LLM support
✓ Enterprise scalability from POC to production

Python-First

Core AutoGen runtime

Tool-Driven

APIs & functions

Observable

Tracing & metrics

Deployable

Docker & cloud

How AutoGen-Powered Systems Operate

A structured multi-agent lifecycle built for reliability and control.

Plan: The Planner agent breaks down complex tasks into actionable steps, defines required tools, and establishes success criteria using AutoGen's conversational framework.

Execute: Solver agents invoke tools, APIs, or custom code, iterating with shared memory to handle dynamic workflows efficiently.

Review: Critic agent evaluates outputs against criteria, flagging low-confidence results for human review to ensure accuracy.

Evaluate & Iterate: Run automated tests, log traces, and refine configurations for production readiness and ongoing optimization.

Deploy & Monitor: Seamless deployment with real-time monitoring, alerting, and auto-scaling to handle varying loads.

Key Features & Capabilities

Multi-Agent Collaboration

Enable multiple AI agents to work together seamlessly with defined roles and communication protocols.

Human-in-the-Loop

Integrate human oversight and approval mechanisms for critical decision points in agent workflows.

Tool Integration

Seamlessly connect agents with external tools, APIs, and data sources for enhanced capabilities.

Memory Management

Short-term context and long-term persistent storage for tasks and knowledge.

Observability

Detailed tracing, evaluation metrics, and logging for performance insights.

Security & Compliance

Encryption, access controls, and compliance tools for enterprise-grade data protection.

Our AutoGen Solutions & Use Cases

AutoGen enables enterprises to deploy AI workflows that are collaborative, intelligent, and measurable. Our solutions cover multi-agent orchestration, human-in-the-loop approvals, and advanced decision-making pipelines.

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Research Copilots

Agents that aggregate data from multiple sources, analyze trends, and generate insightful reports with proper citations.

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Operations Automation

Automate complex business processes with agent collaboration, tool integration, and human oversight.

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RAG Assistants

Provide accurate, grounded responses for customer support, internal knowledge queries, and content creation.

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Decision Support Systems

Intelligent agents that combine data analysis, reasoning, and collaborative decision-making.

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Code Generation & Review

Agents that write, test, and review code for development teams, accelerating software delivery.

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