Background
Instawork operates a labor marketplace for hourly staffing, screening thousands of candidates daily for skills and matching them with businesses hiring talent. The call quality, reliability, and throughput directly affect worker experience and marketplace quality.
The Challenge
Before automating worker screening with Vapi, Instawork needed to manually conduct every screening call. This created three problems.
First, costs scaled linearly with demand. As the marketplace grew, screening costs were projected to reach millions of dollars annually.
Second, quality varied at peak volumes. Consistency suffered when call volumes spiked.
Third, existing tools could not support the technical requirements. Instawork needed high volume real-time voice interactions, multi-modal deployment across mobile and web, and collaboration between engineering, product, and operations teams.
Why Vapi
Instawork evaluated several voice AI tools and chose Vapi in early 2025 as the solution that best met their needs.
Proven reliability at scale: Vapi was built for long-running, production voice workloads. The platform had already handled high call volumes for other customers.
Engineering control without friction: Full control over agent logic, models, and integrations. Flexible configuration across LLMs, STT, TTS, and tool calling.
Built-in dashboard for non-technical teams: Product and operations could iterate on agents without engineering support for every change.
Forward-deployed engineering support: Vapi engineers worked directly with Instawork to ship custom functionality fast.
Compared to ElevenLabs, Vapi offered more robust model configuration and a more complete production platform. Compared to LiveKit, Vapi delivered faster time to value and a higher level of platform abstraction without limiting engineering flexibility.
Instawork worked closely with Vapi's forward-deployed engineering team to launch quickly. The partnership included React Native SDK updates, multi-modal agent support across platforms, and tailored improvements for Instawork's specific screening workflows.
The combination of platform maturity and hands-on engineering support made it possible for us to move fast and operate at real production scale.
Engineering, product, and operations teams on both sides collaborated through a tight iteration loop. This enabled Instawork to move from concept to high-volume production in approximately 30 days.
Outcomes
Scale without degradation: Millions of calls handled with consistent latency, uptime, and call quality under peak load. No re-architecture required as volume grew.
50x Higher throughput: AI agents dramatically expanded the number of screening calls Instawork could run. Proactive filtering earlier in the funnel became possible.
Better worker quality: Using Vapi, Instawork was able to identify top talent more consistently. The number of successful placements as rated by marketplace partners increased by 30%.
85% lower cost: To keep up with demand, Instawork was projecting millions of dollars in costs to use human call screening. On Vapi, they achieved significantly lower cost per call while increasing both the volume and quality of their placements.
Vapi now functions as core infrastructure for Instawork, not an experimental AI tool.
Looking Forward
Instawork continues to rely on Vapi as essential infrastructure for candidate screening. The platform's stability at scale supports ongoing marketplace growth without requiring additional investment in voice AI engineering.
For other teams evaluating voice AI platforms, Instawork's experience shows what matters most at high volume: reliability, engineering control, and a partner that can move at startup speed.
