OpenAI builds and deploys advanced AI models like GPT-4o for autonomous agents and workflows.
NovaSynth
$69/moStarting price
0Popularity
About NovaSynth
NovaSynth simulates real-world user interactions to test AI agents before deployment. It generates synthetic users with personas, moods, accents and adversarial intent, then sends them over real SIP phone calls, LiveKit audio or chat channels. The tool covers scenarios such as frustrated repeat callers, rapid interrupters, non-native speakers and prompt-injection attempts to surface failures during rehearsal rather than after customer exposure. Each synthetic run follows a closed loop: persona and scenario definition, scoring with over 30 voice AI metrics, root cause analysis and validated fixes. NovaSynth operates in pre-production environments, connecting to staging SIP endpoints, test numbers or new agents not yet in production, ensuring no impact on live systems. It supports batch matrix runs across multiple personas and scenarios, concurrency and load testing up to 2,000 concurrent lines, and tool virtualization to replay reads and sandbox writes. The platform captures full traces of each synthetic call and provides detailed metrics and recommendations for improvement.
Key features
- Real SIP phone calls via Twilio, Plivo or Vobiz
- LiveKit and chat channel support
- Persona and scenario generation with goals and moods
- Batch matrix runs across personas and scenarios
- Concurrency and load testing up to 2,000 lines
- Tool virtualization with read replay and write sandboxing
- Over 30 voice AI metrics per call
- Integration with LangChain, LangGraph, OpenAI and Anthropic SDKs
Use cases
- Testing customer support AI agents for edge cases and interruptions
- Evaluating safety boundaries with prompt-injection attempts
- Load testing AI agents under high concurrency scenarios
Pros
- Real telephony and audio with actual latency
- Generates synthetic users with goals, moods and adversarial intent
- Closed-loop testing from persona to validated fix
- Supports SIP, LiveKit, chat and multiple agent frameworks
- Batch matrix runs for comprehensive coverage
Cons
- No free tier for NovaSynth voice and text testing
- Requires system prompt or detailed context for best results
- Production evaluation is a separate post-production module
- Credit-based pricing with no unlimited free option
Frequently asked questions about NovaSynth
What does NovaSynth do?
NovaSynth simulates real-world user interactions to test AI agents before deployment by generating synthetic users with personas, moods, accents, and adversarial intent. It sends these users over real SIP phone calls, LiveKit audio, or chat channels to surface failures during rehearsal rather than after customer exposure.
Who is NovaSynth suitable for?
NovaSynth is designed for teams developing AI agents that interact via voice or chat, such as customer support, loan approval, or debt collection systems. It helps ensure reliability and safety before agents are deployed to real users.
Does NovaSynth work with live production systems?
No. NovaSynth operates in pre-production environments, connecting to staging SIP endpoints, test numbers, or new agents not yet in production. It does not call live production systems to avoid any impact on real users.
What information does NovaSynth need to generate personas and scenarios?
For a single-agent architecture, NovaSynth requires the system prompt, PRD, BRD, workflow docs, or other context explaining what the agent should do. For multi-agent systems, integrating the SDK allows NovaSynth to derive context from traces without needing the prompt directly.
How does NovaSynth handle agent prompts it cannot access?
If the provider does not expose the prompt, users can provide context about what the agent does (e.g., loan approval, customer support) instead. NovaSynth will still generate simulations, evaluations, and reports, though recommendations may be less precise without visibility into the agent's decision-making.
What types of testing can NovaSynth perform?
NovaSynth supports functional testing with personas and scenarios, concurrency and load testing up to 2,000 concurrent lines, and tool virtualization to replay reads and sandbox writes. It captures full traces of each synthetic call and provides detailed metrics and recommendations for improvement.
