Archal: Stateful API sandboxes for agent integration tests

Archal provides stateful API sandboxes for developers building agents and integrations. It fits a team that needs to run a coding agent or CI job against realistic provider-shaped state, inspect what changed and reset the environment without maintaining a pile of shared test accounts.

What it does

Archal’s current product page ↗ describes isolated environments for services such as GitHub, Slack, Stripe, Linear and Supabase. A sandbox can be created, called through REST or MCP, inspected for requests and mutations, and reset to a known baseline. The documented use cases are harness testing, integration testing and agent training or reinforcement-learning rollouts.

The documentation ↗ makes the lifecycle concrete. It says the product currently handles 22 provider-shaped environments, five versioned starting states for each, scoped credentials that expire with the sandbox and explicit state diffs. The same page is clear about the boundary: Archal does not replace the agent harness, model, evaluator, observability tool or CI system. It is the isolated external-service layer those tools can call.

That makes Archal more useful than a thin mock when the bug is in state. A test can create an issue, send a message, update a monitor or change a record, then inspect the mutation and run again from the same starting point. The environments are simulations, not the providers’ live services, and Archal says catalog inclusion does not mean every upstream operation has been reproduced.

Pricing and founder context

The public homepage offers $20 in usage credits without a card, but the retained sources do not expose a standard plan or per-environment price. The purchase question is therefore workload-specific: how many environments, ready minutes, resets and CI runs does the team need, and which provider operations are essential?

The YC profile identifies Aidan Tiruvan as founder and CEO and describes prior machine-learning research at Scale AI and NASA. The launch frames the product as a response to coding agents writing integrations faster than teams can test them. That is a credible problem statement, not proof that every sandbox matches production behavior.

Editorial take

I would shortlist Archal for an agent team whose integration tests are blocked by dirty state, provider rate limits or missing sandboxes. The first proof should be one workflow with a known mutation and reset requirement. If a team needs final confidence against a real provider’s edge cases, Archal is a valuable deterministic layer, not the last production check.

Quick facts

Sources checked

Cohort context

Archal is listed in Summer 2026. In our 2026-09-18 directory snapshot, 119 of 232 listed companies in that cohort have YC’s primary industry label B2B (51.3%). This is a current-directory comparison, not an original intake count or a performance ranking. Nine-cohort dataset.

Public website snapshot

Observed 2026-09-19 16:18 UTC in raw homepage HTML. This records visible metadata and advertised links, not agent execution or product quality.

Public observations · Collection method. Missing links here do not establish that a capability or file is absent elsewhere.