Future AGI vs ToolSpend

Generate personas, scenarios and synthetic datasets to stress-test text and voice agents across many conversation branches before launch.

Combine always-free heuristic metrics, code evaluators and LLM-as-judge scoring, including agentic evaluators that localise errors in RAG and tool calls.

Route traffic across 15+ LLM providers with load balancing, failover and caching, plus 15 built-in rule-based guardrails and ML content moderation.

End-to-end traces, sessions, agent graphs, custom dashboards and alert monitors give real-time visibility into production behaviour.

Track token usage and spend across OpenAI, Google AI, Azure, Bedrock, and other services in one view, so you can see which provider is driving costs.

Project your bill based on current usage patterns so budgets stay under control and end-of-month surprises are avoided.

Get notified when usage jumps, catching retries, broken prompts, or runaway jobs before they compound into large bills.

Recommendations generated from usage and billing signals suggest cheaper model substitutions, idle GPU shutdowns, and retry or error fixes.