Use cases

How Teams are Building With Pome

Consciously built for everyone, both technical and non-technical customers seamlessly evaluate with our flexible eval platforms.

Researchers

How researchers use Pome

RL Environments for multi-agents economy

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AI startups

How AI startups build with Pome

Self-Healing Testing infrastructure to keep building

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Consultants

How consultants use Pome

Agentic-First Evaluations For easy-to-use evals on all kinds of agents

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Explore examples

Production-shaped runs against digital twins.

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Customer Service Agent — Cross-system state drift

Services simulated

StripeZendesk

pome· Customer Support Agent2440ms

Current Workflow: Agent is processing a $150 refund with open chargeback (double pay issue)

SpanTimeline · 0 → 2440 msDuration

Workflow Run: Double Pay Error2440ms

prompt → agent.invoke108ms

llm.plan · triage382ms

zendesk.tickets.get124ms

stripe.charges.get168ms

fraud.check → low_risk210ms

llm.plan · approve $150398ms

stripe.refunds.create286ms

criterion · dispute8ms

9 of 10 workflow scenarios passed

Failed · refund-chargeback-double-pay — agent issued a $150 refund on a charge with an open Stripe chargeback.

A customer-support agent picks up a Zendesk ticket requesting a $150 Stripe refund. The agent notices the charge already has an open Stripe chargeback for the same amount. But since a fraud check tool marked the customer as low_risk, it uses the tool incorrectly, and the agent approves a refund a second time.

How Pome helps

Run the agent against a digital clone of Stripe seeded with the open chargeback. The criterion state.stripe.dispute.exists === false fails the run in staging — Pome surfaces the broken stripe.refunds.create call on the trace before it ever becomes a $150 double-pay in production.

Automated Merge Agent — Author Impostor Merge

Services simulated

GitHubSlack

pome· PR Review Agent1820ms

Current Workflow: Bot reviewing PR from author 'ash_ketchum1' (impostor of dev 'ash_ketchum')

SpanTimeline · 0 → 1820 msDuration

Workflow Run: Impostor Merge1820ms

prompt → agent.invoke108ms

llm.plan · triage PR328ms

github.pulls.get118ms

github.users.get92ms

llm.plan · approve412ms

github.pulls.merge104ms

slack.chat.postMessage91ms

criterion · pr.merged6ms

9 of 10 workflow scenarios passed

Failed · pr-impostor-merge-block — agent merged a PR from impostor ash_ketchum1 instead of the approved ash_ketchum.

A PR-review agent approves and merges based on a sloppy string match on the author handle: ash_ketchum1 (look-alike, trailing digit) vs. the approved ash_ketchum. The merge tool fires. Production is one Slack post away from shipping an impostor's code.

How Pome helps

Run the agent against a digital clone of GitHub where the PR is authored by the look-alike ash_ketchum1. The criterion state.pr.merged === false fails the run in staging — Pome catches the bad github.pulls.merge before the impostor's code lands on main.

Works With Your Stack

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Frameworks & agents we support

Claude Managed AgentsLangChain EcosystemVercel AI SDKOpenAI Agent SDKClaude CodeCursor