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Agentic workflows

Siren can naturally become more agentic over time. The important constraint is that agentic features should sit on top of real execution and risk infrastructure. They should not become empty AI decoration.

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What “agentic” means in Siren

In Siren, agentic features should help traders:
  • decide
  • execute
  • review
  • monitor
That means copilots and background intelligence, not just chat.

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Post-trade agent

One of the strongest early agentic surfaces is post-trade analysis. After a trade, Siren could generate:
  • what was attempted
  • what venue and route were used
  • whether the trade was full or partial
  • what failed
  • what the trader should try next
This is especially valuable when a route degrades or a trader keeps retrying the same behavior.

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Portfolio risk agent

A portfolio agent can watch for:
  • correlated positions across related events
  • concentration into one outcome cluster
  • contracts approaching resolution
  • positions that may be hard to exit at size
This turns Siren into an active warning layer instead of a passive dashboard.

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Execution copilot

An execution copilot could eventually suggest:
  • smaller sizing steps
  • alternative timing
  • whether to wait for better conditions
  • whether to reduce exposure before resolution
The key is that suggestions must be grounded in actual route and history data.

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Daily intelligence brief

Another natural surface is a recurring brief:
  • largest exposure changes
  • new execution failures
  • markets nearing resolution
  • changes in venue readiness
This gives the trader one place to catch up instead of hunting across screens.

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Product principle

Siren should only make agentic promises where it has enough execution and risk data to be credible. The order matters:
  1. instrument trade attempts
  2. capture failure reasons
  3. frame correlated risk
  4. generate agentic guidance from the real data