Papaya is the optimization engine for AI agents. Engineers don't have time to continually improve the agents they've shipped — the context bloat, overly chatty subagents, and broken tool calls sit in production traces nobody reads. With Papaya they connect their agent directly via SDK, get actionable recommendations on how to improve quality, latency, and cost, and the ones they approve are pushed to production as pull requests. Papaya runs 200+ research-backed analyses across context, prompts, prompt caching, subagents, and tool calls. Every recommendation is ranked by impact and comes with the production runs that produced it — typically a 10%+ quality improvement on the first workflow analysis.Papaya is an optimization platform for teams running production AI agents. It connects to agent traces through a lightweight SDK, existing observability tools, or exported datasets, then automatically maps workflows and analyzes prompts, context, memory, retrieval, tool calls, models, trajectories, and outcomes. More than 200 research-backed analyses identify recurring failure patterns and improvement opportunities across thousands of runs. Papaya ranks every recommendation by its expected effect on quality, latency, and cost, and shows the exact production evidence behind each finding. Teams remain in control: they review proposed changes, receive proactive alerts in Slack, and approve fixes before Papaya opens implementation pull requests. The platform also supports automated trace detection, an interactive LLM judge, observability dashboards, executive summaries, and continuous monitoring. Papaya helps engineering teams move beyond dashboards by turning production telemetry into prioritized, measurable improvements that compound as new traces arrive and additional fixes are shipped without adding operational overhead.
Pricing and access
Developer: Free — 1 agent and up to 10,000 traces per month. Business: $500 per month — up to 3 agents and 1 million traces per month. Enterprise: Custom pricing — unlimited agents.
