AgentGuard gives production AI agents a safety layer: replay every run, trace every tool call, catch risky behavior, test prompt changes, and monitor cost before an agent surprises your users.
User asked for an $800 refund after a delayed shipment.
Most teams can read the response. Few can explain the path that produced it. That gap is where production incidents, surprise bills, and customer trust problems begin.
A customer receives a bad answer, but your logs only show the final output. AgentGuard records the prompt, model calls, retrieved context, tool calls, and policy checks in one replayable timeline.
Agents do not just talk anymore. They refund orders, send emails, update CRMs, delete records, and trigger workflows. AgentGuard flags risky tool calls before they become expensive mistakes.
A small prompt edit can change which API an agent calls or whether it asks for approval. AgentGuard makes prompt regression testing part of the release flow for production AI agents.
AgentGuard combines agent replay, guardrails, regression testing, and cost monitoring so developers can move from agent demos to reliable workflows.
Replay every agent run as a clean timeline with prompts, LLM calls, retrieval context, tool inputs, tool outputs, errors, latency, and cost.
Create rules for refunds, deletion, outbound email, sensitive data, cost limits, prompt injection attempts, and human review requirements.
Build test cases for expected behavior, forbidden tool calls, and required approvals. Compare agent versions before shipping prompts, models, or tools.
Track token usage, model spend, tool retries, slow steps, loop patterns, and cost spikes by project, environment, customer, and agent version.
The first version of AgentGuard is focused on developers and small teams that need production confidence, not another agent builder.
Enforce approval rules, replay support incidents, and monitor whether your AI support agent followed policy before touching CRM, refund, ticketing, or email tools.
Trace outbound messages, quote generation, CRM updates, meeting booking, and qualification logic. Flag risky claims before a sales agent sends them.
Monitor coding agents that read files, call tools, create patches, run tests, or open pull requests. Replay the exact sequence that produced an incorrect change.
Tell us what kind of agent you are shipping. We are inviting developers building support agents, sales agents, coding agents, and internal workflow agents first. Early users will get direct onboarding and influence the SDK.