OpenAI Agents SDK
A free, open-source developer library from OpenAI for building custom AI agents in code, with tools and handoffs between agents.
A free, open-source framework from Microsoft Research for building systems where several AI agents talk to each other to finish a task.
AutoGen is a free, open-source framework for building AI agents that communicate with each other to complete a task. It offers three ways to build: AutoGen Studio, a web interface for prototyping agents without code; AgentChat, a Python kit for conversational multi-agent apps; and Core, a lower-level, event-driven framework for complex systems. Developers can connect agents to OpenAI's Chat Completion and Assistant APIs, add tools through the Model Context Protocol, or MCP, run generated code safely inside Docker containers, and run distributed agents that communicate over gRPC, a method for connecting services across machines. It comes from Microsoft Research rather than a product team, so expect faster change than in a fully supported commercial product.
This fits a technical team that wants to experiment with multi-agent designs, such as two agents that critique and revise each other's work, before committing to a heavier commercial platform. AutoGen Studio is a reasonable way to prototype an idea without full coding effort, and AgentChat and Core give more control once the design is clearer. There is no license cost, but budget developer time for setup and for keeping up with a framework that changes often, plus the underlying model API costs, since AutoGen does not include model access. The main risk is stability: expect breaking changes between versions and plan testing time before each upgrade.
These estimates cover licensing, setup, integrations, staff time, security, administration, and support.
| Cost measure | Low | Base | High |
|---|---|---|---|
| First-year total | $57.8K | $91.9K | $149.2K |
| Three-year total | $121.4K | $184.7K | $288K |
| First-year cost per unit | $57.8K | $91.9K | $149.2K |
| Average annual cost per unit (over three years) | $40.5K | $61.6K | $96K |
| Component | Low | Base | High |
|---|---|---|---|
| Licensing and usage | $16.5K | $22K | $29.7K |
| Implementation | $9.6K | $16K | $27.2K |
| Integration | $12.1K | $22K | $39.6K |
| Staff time and change management | $6.3K | $9K | $12.6K |
| Security | $4.9K | $7K | $10.5K |
| Administration | $3.8K | $5K | $6.8K |
| Support | $1.9K | $2.5K | $3.4K |
Estimate assumptions: Based on 1 production deployment. This is a planning allowance, not verified product pricing. Confirm the vendor’s billing unit and current price or quote before budgeting.
Benefits have not been estimated: The current research does not estimate potential savings, return on investment, or how long it would take to recover the cost. Earlier benefit estimates are excluded.
Confirm current product identity, commercial packaging, data processing terms, sign-in and access rules, retention, integrations, support model, implementation effort, and rollback conditions.
Verify identity, package, availability, ownership, pricing, and security evidence before approving a pilot
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
Define what success looks like for a test of AutoGen and assign someone to lead it.
Once the requirements above are met, compare a small trial with how your team works today.
Track adoption, output quality, business results, and actual costs against the estimate.
Use the results to decide whether to stop, adjust, or expand the pilot.
Confirm encryption, how the vendor uses your data, customer data separation, how long data stays and how to delete it, activity records, sign-in and user setup, where data is handled, other companies that process data, past incidents, and what your team must manage.
Review before rollout: confirm how to export your data, revoke access, and return to your existing workflow. Assign an owner and test the rollback plan before expanding use.
Do not approve a pilot yet. Verify the current product identity, package, availability, owner, pricing, and security evidence; then define one workflow, a baseline, and rollback criteria.
A free, open-source developer library from OpenAI for building custom AI agents in code, with tools and handoffs between agents.
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