Innovation at Parloa.

Personal AI agents are now contacting support on a customer’s behalf. Open protocols help them connect, authenticate, and authorize. But secure access doesn’t guarantee resolution: agents don’t know your internal processes, and you need to verify what the customer authorized. Parloa's Personal Agent Middleware helps turn requests handled by personal AI agents into reliable service. Working across personal-agent providers, protocols and backend systems, it applies your rules, controls permissions and guides tasks through to resolution. Your brand stays in control, with fewer integrations, checks on risky actions and a clear record of what happened.

Most customers are treated like strangers every time they call, re-explaining who they are and what they already said. Their intent goes uncaptured. Parloa Context Intelligence is a customer understanding and decision layer that lets your AI agents remember the facts from your data and customer conversations, carry that context into the next conversation on any channel, and choose the right thing to do in the moment.

Each conversation starts where the last one left off, leading to relationships that grow stronger over time.

CX leaders need one clear signal of customer experience that they can track over time. CSAT and NPS rely on surveys few customers complete, and say little about why a score changed. Parloa Relationship Score is a weighted score out of 100, representing your AI agents' impact on customers across every conversation, with drill-downs into every contributing factor to understand performance and guide improvements. Built on Parloa Lens and its LLM-based evaluation of conversations, Parloa Relationship Score brings together resolution, effort, accuracy, trust, emotion, and agent conduct into one number, weighted by how they shape the experience.

Writing agent tests manually is slow, and only covers what someone thought to test. Parloa Automated Simulations & Evaluations drafts a tailored test set in minutes whenever an agent is created or changed. It covers intents, tool calls, handoffs, and guardrails, and it can draw on anonymized historical transcripts, so tests reflect how customers actually speak to an agent. Your experts review and approve every test before it's used.

Passing an evaluation doesn't tell you whether a new agent version beats the one running today. Parloa Automated Agent A/B Testing runs old and new agent versions against the same evaluation scenarios and quality metrics, with no extra setup. Results appear side by side, showing where the new version improved, regressed, or stayed the same. Every score traces down to the conversation behind it, so you can weigh the trade-offs before you release.