Improve the whole agent — not just the prompt.
Instructions, tools, rules, data access, workflows, and policies. Xplore evaluates, trains, deploys, and controls across every layer of agent behavior.
Everything that shapes agent behavior is scored, versioned, and improvable.
Most platforms tune prompts. Xplore treats the entire agent configuration as a trainable surface — scored, versioned, and improved across every iteration.
System prompts, task descriptions, behavioral guidelines — the words that shape agent behavior.
Python functions, API integrations, data connectors — the capabilities an agent can invoke.
Escalation policies, safety guardrails, compliance constraints — the boundaries agents operate within.
Which databases, APIs, and services the agent can reach — and how it queries them.
Step ordering, branching logic, parallel execution — the structure of how agents work.
Promotion gates, cost limits, certification requirements — the governance layer over everything.
Deeper training unlocks more of the agent for optimization.
From prompt tuning (L0) to team synthesis (L5). Each level unlocks more of the trainable surface. L0–L3 are live today. L4–L5 on the roadmap.
Scores drive training. Training produces versions. Monitoring closes the loop.
Evaluate, [Re]train, Deploy, Control — each verb operates across the full trainable surface. The architecture ensures they connect: evaluation results feed training, training produces deployable versions, deployment gates enforce standards, monitoring feeds back into retraining.
40+ composable evaluators run against the full trainable surface. Not just prompt output — tool usage, rule compliance, workflow correctness.
Six depth levels from prompt tuning to team synthesis. The trainer edits every surface, not just instructions.
Gated release with regression certifications. Every version carries a full evaluation snapshot.
Live certifications, drift detection, cost tracking. The same evaluation chains used in training, running continuously in production.
Your existing stack stays. Xplore adds the reliability layer.
Your LLM provider stays. Your data platform stays. Your orchestration framework stays. Xplore sits at the runtime layer — resolving agent configuration, executing evaluation, managing training, and enforcing production controls.
See how the pieces fit together.
Evaluate, train, deploy, control — one integrated loop on your infrastructure.