Autonomy vs Banksia

Autonomy and Banksia are both agent frameworks tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Autonomy

The core loop — AgentLoop — runs up to a configured step ceiling, selects from 15 bundled procedural skills, ranks candidate actions across five weighted dimensions using beam search, executes through ActionGateway with LOW/MEDIUM/HIGH risk labels, then evaluates and learns. Every event in that chain is stored via event sourcing, so the full run is replayable. The learning loop drafts new skills after a successful run and queues them for review rather than auto-applying them. The wall appears when you need agents running in parallel or sharing state across concurrent sessions — the architecture is single-loop, single-goal. Teams that outgrow that model start wiring external orchestration around it.

Banksia

Banksia is an open-source, MIT-licensed framework for building and running multi-agent AI teams on local or self-hosted infrastructure. The core workflow starts with agent…

Attribute	Autonomy	Banksia
Pricing	Paid	—
Price	$75/mo	—
Free trial	7 days	No
Open source	Yes	No
Has API	Yes	No
Self-hosted option	Yes	No
Platforms	Python 3.13	—
Pros	ActionGateway classifies every tool call as LOW, MEDIUM, or HIGH risk and routes it through an ApprovalPolicy before execution, so you get a stop point before an agent overwrites a file or calls an external API in an unreviewed context. Full event-sourcing audit trail from run_started through run_finished, which means a failed or unexpected run can be replayed step-by-step rather than reconstructed from logs after the fact. LearningLoop drafts new ProcedureSkills after successful runs and queues them for human review rather than auto-merging, so the agent's skill library grows without accumulating unreviewed automation. RecipeEngine promotes repeated successful action patterns to reusable recipes after two confirmed successes, so the LLM is not re-reasoning from scratch on tasks the agent has already solved before. Provider-agnostic LLM configuration across nine endpoints including local Ollama, so switching from a cloud provider to a local model for cost or privacy reasons is a config change rather than a code change.	—
Cons	The AgentLoop is a single-goal, single-thread loop with a hard step ceiling (default max_steps=12). Tasks that require parallel subtasks or concurrent agent coordination have no native path — teams that need multi-agent parallelism add an external orchestration layer, which means maintaining two systems. The skill library and RecipeEngine improve through accumulated runs, but on first deployment against a novel domain, the agent has no relevant skills or recipes yet and falls back entirely on LLM proposals. Teams handling narrow, high-specificity domains report writing custom ProcedureSkills before production use. Browser tooling depends on Playwright headless Chromium and is opt-in with MEDIUM risk classification applied to all MCP-imported tools by default. Teams that need fine-grained risk overrides on external tools must configure ApprovalPolicy manually — the docs describe the interface but provide precious little guidance on policy design for production environments, which is the condition under which teams switch to frameworks with more mature policy tooling.	—

Bottom line

Autonomy is open source; only Autonomy exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Autonomy and Banksia?

Autonomy is Paid and open source, while Banksia is unknown pricing. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Autonomy better than Banksia?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.