Comparison · Agent controls · AI traffic evidence

Agent controls and traffic evidence solve different problems.

Agent governance toolkits help control what an agent can do inside your application. Talon helps control what AI traffic leaves your environment and produces signed evidence for security, DPO, customer, and auditor reviews.

Run Talon demo See evidence model All comparisons

Choose the layer

Agent action policy → agent toolkit
AI traffic evidence → Talon
Both risks          → use both layers

Agent actionsAI egressPII controlsEU sovereigntySigned evidence

Short answer

They are complementary, not interchangeable.

Start with an agent governance toolkit when you are designing the agent runtime and need action-level controls. Start with Talon when you already have LLM apps, agents, bots, or vendor workflows and need to prove what crossed the model/provider boundary.

🏗️

Agent governance toolkits

Best for tool execution, sub-agent behavior, permissions, and action policy inside agent code.

🇪🇺

Talon

Best for PII controls, EU routing, cost caps, provider-boundary control, and signed evidence across AI traffic.

🤝

Together

Use both when you need action controls and verified evidence of what left your environment.

Decision matrix

Which path fits your situation?

Your situation	Recommended path
You are building a new agent and need deep action-level controls.	Start with an agent governance toolkit.
You already have AI traffic going to model providers.	Start with Talon.
You need to answer DPO, security, customer, or auditor questions.	Use Talon and export signed evidence.
You need both action controls and provider-boundary evidence.	Use both layers together.

Evaluate Talon

Test one AI workflow in minutes.

Route one OpenAI-compatible workflow through Talon, send test PII, inspect the policy decision, export the evidence, and verify the signature.

Run the demo Use the checklist