After a simulation run, PinPole's AI engine analyses your architecture and returns a prioritised set of findings - missing services, misconfigured concurrency, structural risks - each with a rationale, an expected impact, and a one-click implementation button.
The AI engine reads your architecture canvas and the live simulation results together. It doesn't scan a static diagram - it sees what actually happened under load and surfaces findings specific to your services, your configuration, and your traffic pattern.
Get Recommendations in the simulation panel. The engine analyses your canvas and simulation results and returns a ranked set of findings - typically 4–8 items for a new architecture. Each finding includes a severity level, a category, a full rationale, and an expected impact.Implement - the change is applied to the canvas immediately. New services are added and wired. Configuration changes are applied to the relevant node.Refresh Recommendations to re-analyse the updated architecture. New findings may emerge that were not visible before - the engine works against the current state.Every recommendation is categorised, severity-ranked, and expandable. Read the full rationale, review the expected impact, then implement directly from the panel - no manual canvas edits required.
Background Worker Lambda shows 892 cold starts during the simulation run at 1,000 RPS. Provisioned concurrency ensures worker instances are pre-initialised, preventing request queuing during burst periods.
DynamoDB read patterns show high repetition at current load. Adding a DAX cluster in front of DynamoDB will serve repeated reads from memory, reducing DynamoDB read unit consumption and improving p99 latency on read-heavy paths.
Request Processor Lambda calls downstream services without retry logic. Under load, transient failures from DynamoDB or RDS will surface as hard errors. Exponential backoff with jitter absorbs transient failures without amplifying downstream pressure.
Recommendations are returned in severity order - address WARNINGs before INFOs. Each card shows enough context to act, with the full rationale one expand away. The Implement button applies the change immediately: services are added, wires are drawn, configuration is updated.
Every finding is assigned a severity level that signals urgency. The ordering is deliberate - address WARNINGs before INFOs, and re-simulate between each change.
A configuration that represents a real failure risk or significant cost inefficiency at the simulated load. These findings require action before deployment - they are not advisory.
An improvement opportunity that is not blocking but should be addressed before production - these findings represent meaningful performance or cost gains that are not urgent at current load.
No manual canvas edits. No digging through documentation to figure out how to wire a new service. The Implement button applies the recommendation directly - new services appear on the canvas, connections are drawn, and affected node configuration is updated.
Each recommendation maps to a specific, reversible change on the canvas. Implement applies it immediately - the change is visible in the canvas, and the simulation state is reset so your next run reflects the updated architecture.
add service recommendations, the new node appears on the canvas connected to the correct upstream and downstream services. No manual wiring required.modify config recommendations, the affected node's properties are updated in place. Open Node Configuration to inspect the change before re-running.architecture recommendations, connections are re-routed, protective patterns are applied, and async paths are introduced - exactly as specified in the recommendation rationale.A few habits that make the optimize loop measurably more effective - drawn from the recommendation patterns that emerge most frequently in real simulation sessions.
Refresh Recommendations to ensure the next set of findings reflects the updated architecture.Recommendations are available on all plans. Free includes 3 AI calls per month. Pro, Team, and Enterprise include unlimited calls. Additional AI credits are available as add-ons on any paid plan.
Design on the canvas, run a simulation, and get recommendations before a dollar is spent on AWS. Every finding comes with a one-click fix.