Make.com verdict · build Solution request

Batch executor for Make that runs queued scenarios in parallel

Built for Make users processing large job queues.

“Hi, I have a queque of several hundred items. Is there a way to run them all at once opposed to clicking every time run and waiting for the scenario to complete…”

The receipts — real demand

“Hi, I have a queque of several hundred items. Is there a way to run them all at once opposed to clicking every time run and waiting for the scenario to complete? Thanks!”
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6.3 / 10 · demand score
Pain 7
Willingness to pay 4
Feasibility 8
Specificity 8
Audience 8
Competition 7

Why this is a gap

Surfaced from a high-intensity complaint with clear willingness to pay and a specific, reachable audience.

The market

Make users processing job queues of hundreds+ items who currently click run repeatedly and wait for serial execution. No search volume data, but the pain signal is specific and repeated, suggesting an active subset of Make's user base faces this friction regularly.

Competition & the opening

Wedge play crowded — win on a narrow angle Moat 3/10 · thin angle Market 4/10 · small niche
Crowded market · 7/10 vs Make (Integromat) native scheduling & parallel branchesMake Operations Queue (built-in scenario execution control)n8n (self-hosted, native parallel execution + queue mode)Pipedream (parallel event workers, native batch processing)Activepieces (open-source, parallel flow runs)Celery + custom Make API wrapper (OSS DIY stack)

Make natively offers scheduling and parallel branches; Make Operations Queue provides built-in scenario execution control; n8n, Pipedream, and Activepieces all have native parallel execution and queue modes. The gap is Make users want a single-click batch executor without rebuilding workflows—a thin wrapper, not a new platform. Competition is crowded (7/10) and most incumbents already solve this a

What's hard to build

Make's API and webhook architecture allow external queuing, but integrating tightly with Make's scenario state, monitoring, and error handling requires reverse-engineering undocumented APIs or tight partnership. Scaling to handle hundreds of parallel runs without hitting Make's rate limits or infrastructure caps is non-trivial.

Why now

Make's native queue system lacks true parallel batch execution, leaving power users stuck with sequential or manual workarounds.

How you'd monetize

freemium tier with usage limits, $9-15/mo for 10k+ parallel runs