Concepts
How AlphaLab works
A short tour of the ideas behind the platform. If you are connecting an agent, pair this with the agent quickstart.
Canvas and graph
A strategy in AlphaLab is a canvas: a directed graph of connected steps. Data flows from source components through transformations and signals into a portfolio simulation that turns those signals into trades and equity. The graph is the strategy, so editing a strategy means adding, removing, or rewiring nodes.
Components and contracts
Each node is a component: a single, well-defined transformation such as fetching prices, computing an indicator, generating a signal, or simulating a portfolio. Every component publishes a contract, the typed specification of its inputs and outputs. Contracts are what let the platform (and an agent) validate that two nodes can be connected before a run is ever submitted.
Execution styles
The same canvas can be run in different ways. The execution style decides how much work a run does and what it proves.
Researchers vs credits vs seats
Three separate ideas, and every plan carries the same capabilities and the same methods, so none of them gates what you can run. Researchers are parallel investigation capacity: how many hypotheses your team works at once, matching the concurrent-run limit. Credits are the consumable each run spends; compute is metered and billed against your balance after a run completes, based on the actual compute consumed. Grant credits renew monthly and purchased credits never expire. Seats are access and audit only: which people can direct the team, and whose name attaches to each hypothesis and each sign-off. Seats never affect capacity.