Parloa’s blueprint for reliability in production

Managing highly sensitive medical and financial data makes healthcare one of the most regulated industries. Combined with the direct impact on human life, it seemingly makes it one of the hardest to automate. A recent report from McKinsey found that inaccuracies, biases, and flaws combined with security, regulatory compliance, and difficult workflow integrations are among the top barriers healthcare leaders face in scaling generative AI across their organizations.

At the same time, interest in agentic AI for healthcare is quickly accelerating. And 76% of McKinsey’s respondents named administrative efficiency as one of the areas where multi-agent AI workflows have the greatest potential.

When AI can seamlessly connect with the systems already in place, it’s able to mitigate concerns and deliver secure, personalized experiences. That’s why Parloa integrated with Epic, one of the world’s largest global electronic health record (EHR) providers. By working within a pre-existing, well-established system such as Epic, Parloa’s AI agents are able to act through governed, permission-aware actions that preserve operational integrity while delivering a better patient experience.

The process of building this integration led us to create a blueprint for reliable AI that rests on four key pillars: identity and permission alignment, context and workflow state, actions with guardrails, and auditability and human handoff.

Pillar 1: Identity and permission alignment

Identity alignment creates predictable behavior. Permission alignment creates safe behavior.

Whether in person, online, or over the phone, the first step to any patient experience is authentication. This doesn’t (and shouldn’t) change with AI agents. A production-grade AI agent validates identity in ways that match the health system’s pre-existing policy and risk tolerance.

First, the agent performs patient identity validation using approved demographic and contextual signals. From there, it may request additional explicit confirmation (e.g., name and date of birth) when a workflow requires sensitive actions. Throughout the patient interaction, the agent uses scoped authorization aligned to Epic’s security model for staff-facing operations. In doing so, the agent doesn’t deviate from what has been established as standard, keeping interactions safe and secure.

Pillar 2: Context and workflow state

Context and state create continuity. Continuity creates completion.

When a system such as Epic is so deeply integrated into a business, not leveraging it is both a disadvantage and a risk. By referencing Epic as a source of truth, agents retrieve the minimum context required to complete the patient’s intent. Beyond that, the agents can leverage this context to deliver more personalized patient experiences, whether that’s interpreting the patient’s questions, confirming details with them, or presenting options.

The integration treats Epic as the system of record, and it models agent behavior around Epic workflow state transitions. Parloa’s AI agents track workflow state explicitly, including required confirmations, pending decisions, and escalation conditions, adhering to healthcare system guidelines. By treating Epic workflow objects as the canonical representation of status and progress, agents optimize existing processes rather than altering what’s already been established.

Finally, the integration doesn’t operate in only one direction. Conversation context is written back to Epic, updating the relevant records, and ensuring that patients won’t have to repeat themselves the next time they call.

A few examples of this in practice:

• An appointment changes and the schedule reflects the update.

• A reminder confirms the visit and the disposition becomes visible to staff.

• A billing inquiry resolves and the next step routes appropriately.

• A portal issue progresses and a task lands with the right team.

Pillar 3: Actions with guardrails

Bounded actions and deterministic guardrails earn operational credibility.

Securely managing a large volume of support inquiries daily requires careful curation of agent actions and guardrails. Parloa’s integration leverages Epic-supported interoperability patterns such as FHIR and SMART on FHIR where applicable, enabling structured access to the data objects that power patient access workflows. These workflows serve as guidance, defining approved action sets, such as appointment confirmations, rescheduling, or task routing.

Furthermore, each action includes prerequisites, validations, and user confirmations to ensure the right workflow is being activated for the right reason and the right patient. Escalation triggers are established to represent clinical, operational, and policy boundaries.

Pillar 4: Auditability and human handoff

Auditability reduces rework. High-quality handoffs reduce friction for patients and staff.

Healthcare operations depend on traceability. Any nurse or doctor should be able to log in to a system such as Epic and immediately be able to decipher when certain treatments happened, why they happened, and who orchestrated them. In our Epic integration, we ensure our AI agents support accountability through structured outputs. Every workflow produces a structured outcome record that captures intent, actions, and resolution state, and syncs back into Epic. When support inquiries do need to be handed over to a human agent, that human agent receives a concise summary, key data points, and recommended next steps from the AI agent, so they aren’t starting from scratch. Finally, operational monitoring tracks completion rates, escalation reasons, and quality signals to further optimize the integration moving forward.

Reliability in production relies on a strong foundation

Designed from our experience integrating with a highly sensitive medical system, these four pillars serve as the foundation to reliable AI in production. With identity and permission alignment, context and workflow state, guardrails, and auditability comes reliable connectivity, predictable governance, and deployment pathways that align with even the most sensitive health system operating models.

With these pillars in place, AI transitions from something healthcare workers want to use to something they can safely implement and quickly benefit from.

Epic is a registered trademark of Epic Systems Corporation.