Choosing the right speech-to-text API for voice agents involves understanding specific requirements beyond standard transcription needs, including sub-300ms end-to-end latency to ensure natural conversational flow, high accuracy on business-critical tokens, and intelligent semantic endpointing to handle realistic speech patterns. The guide emphasizes testing APIs with actual business data to ensure performance in real-world scenarios, and highlights integration challenges, such as compatibility with orchestration frameworks and the quality of the developer experience, which can significantly impact implementation timelines and long-term costs. Additionally, it advises evaluating vendors based on their commitment to voice AI, total cost including hidden expenses, and risk management factors such as financial stability and industry compliance. For successful deployment, it's crucial to conduct a focused proof of concept tailored to specific use cases, prioritize features that align with business needs, and choose providers offering robust analytics and optimization tools for ongoing performance tuning.