Every enterprise runs on workflows — multi-party, document-heavy, exception-prone. Today, humans absorb the friction: chasing documents, routing exceptions, moving data between systems. That is not a people problem. It is an agentic AI problem.
Agents change the equation. Not AI that assists the people running operations — AI that runs operations. End to end. Without being asked. Across every party, every system, every wait state in the workflow.
The shift from SaaS to Enterprise Agentic AI is the most consequential infrastructure transition since cloud. The companies that get there first will not be going back. PLRX exists to be the platform that makes that transition real.
For our team, the trajectory is clear: fully autonomous operations.
Michael founded PLRX on the belief that the shift from SaaS to Enterprise Agentic is the most consequential infrastructure transition since cloud, and that operations — ultimately — will run themselves.
A technologist and entrepreneur at his core, Azam drives the technical vision of the company — combining deep engineering expertise with a relentless focus on agentic AI orchestration, ensuring the infrastructure powering tomorrow's autonomous systems is built to scale, adapt, and endure.
Nitesh leads the development of our agentic platform, combining a product-first mindset with technical expertise to deliver autonomous solutions. He is dedicated to building the infrastructure that allows AI agents to operate as proactive partners in achieving complex business objectives.
With a 15-year background in information security, Erik specializes in the governance, compliance, and security of agentic AI workflows. Through collaborative leadership, Erik ensures that as AI systems shift from simple tools to independent actors, they remain securely anchored to corporate compliance frameworks.
Helen is an enterprise technology and revenue growth leader with 20+ years of experience in enterprise sales, automation, digital transformation, and AI-enabled growth strategy, specializing in GenAI and autonomous agent technologies that drive scalable revenue and operational efficiency.
Ben sits at the intersection of enterprise and AI. A 20-year enterprise healthcare IT veteran, he has translated business needs into custom software solutions and stewarded a systems portfolio at $120M revenue scale. He co-founded an AI-native company and weaves AI and agents throughout his own workflows.
Jonathan brings over 12 years of healthcare IT expertise and deep clinical workflow insight to the development of the PLRX agentic platform. An empathetic leader with an instinct for uncovering what clients actually need — not just what they ask for — he engineers product solutions that consistently go beyond the original brief.
Enterprise Agentic AI needs an operating layer that doesn't exist. We assembled the team to build it first.
The founding team came out of Chicago's derivatives markets, where they built the low-latency clearing infrastructure that kept algorithmic trading firms operating at tens of thousands of transactions per second — smart order routing, real-time messaging, in-memory state, and ultra-fast decision logic under conditions where a single missed event meant real financial consequences.
That infrastructure discipline carried into retail, where the core team built the real-time operational backbone for brands and retailers — synchronising inventory, routing orders, and connecting B2B and B2C ecosystems at the speed the market demanded.
PLRX is the third act. The same founding instinct — that execution infrastructure is what separates systems that hold up in production from those that don't — applied to the most consequential transition in enterprise software since cloud: the shift to agentic AI autonomous operations.
These are not values we aspirationally adopted. They are the operating principles that emerged from building production-grade agentic systems against the constraints that real healthcare, financial services, and supply chain workflows impose.
A platform that works in a demo and fails in a 5-day payer adjudication cycle is not a platform. Everything we build is judged by what happens when it runs against real payers, real providers, and real consequences. The demo is never the standard.
The model does not fail. The stateful execution layer underneath it does. We invest disproportionately in infrastructure — durability, fault tolerance, observability, exactly-once semantics — because that is where production workflows break, and where ours do not.
You cannot automate a workflow you do not understand. The PLRX team includes people who know why an NCCI edit rejects a code pair, what the difference between an EDI 278 and a FHIR R4 prior auth request is, and why a Title XIX document requires a specific signature placement. That depth is not learnable from documentation alone.
A2A and MCP are open protocols — inspectable, composable, and portable. Your agents talk to any system that speaks the same standard. What we invest in is the execution quality on top of those protocols: the durability, the fault tolerance, the audit trail. Open by design. Engineered for production.
HIPAA compliance, BSA exam readiness, WORM audit logs — these are not features added to meet a checklist. They are architectural constraints that shaped the platform from the first line of code. Security and compliance cannot be retrofitted. They must be designed in.
A solution that works but is hacky will break in a way you did not anticipate. We require elegance — not as an aesthetic preference, but as a correctness criterion. If a fix feels expedient, it is not yet correct. Implement the elegant solution.
Ready to deploy autonomous operations across healthcare, financial services, and retail.
If you want to deploy the platform on your workflow — or join the team building it — we want to hear from you.