ParkNova Ventures LLC

Private investment company  ·  Enterprise agentic AI

Agents that finish the work. In industries that require proof they did.

ParkNova Ventures backs enterprise agentic AI — software that completes a task end to end rather than drafting it — and the companies putting it to work in healthcare, pharmaceuticals, and medical technology.

Enterprise agent platforms
Healthcare operations
Pharma & life sciences
Medical technology

Run 4471-C  ·  Prior authorization  ·  Specialty infusion Audit trail retained · 7 yr
09:14:02▸retrievechart, last 18 monthsok 1.4s
09:14:04▸extractdiagnosis codes, failed step therapyok 0.9s
09:14:05▸checkpayer policy, current revisionok 0.6s
09:14:06▸composeletter of medical necessityok 2.2s
09:14:08⏸escalateclinician sign-off requiredheld
09:22:41✓approvereviewed and signed, attendingsigned
09:22:43▸submitpayer portal, confirmation capturedok 3.1s
8m 41s elapsed  ·  7 steps  ·  1 human touch  ·  prior median 3 days
Illustrative run trace. The record is the product.

Thesis

Most enterprise AI is still stuck at suggestion. A model drafts, a person checks, and the headcount never changes.

Agentic systems break that pattern only when an organization can trust them to complete a task without supervision. In healthcare, pharma, and medical technology, trust is not a feeling — it is a requirement with a paper trail behind it. Every action needs a record, every exception needs a defined escalation path, and someone with a license needs to be on the approval line.

The compliance burden is usually described as the reason these industries adopt late. We think it is the moat.

Building an agent that survives a validation review, a payer audit, or an inspection is slow, unglamorous work that general-purpose tools cannot shortcut. The companies willing to do it inherit workflows nobody else can enter — and they sell into operating budgets, where the money is recurring, rather than innovation budgets, where it is not.

We invest in the platforms that make these agents governable, in the applications built on top of them, and in the operators deploying agents inside their own businesses to run at a cost structure their competitors cannot match.

Where we invest

One platform layer, three regulated markets

Application layerAgents doing named jobs

Healthcare

Administrative work inside providers and payers, where hiring another coordinator is not a realistic option.

  • Prior authorization and appeals
  • Revenue cycle, coding, denials
  • Intake, scheduling, referrals
  • Clinical documentation
  • Eligibility and benefits

Buyers: health systems, MSOs, ASCs, payers, billing companies

Pharma & life sciences

Document-heavy, deadline-bound processes where the cost of a miss is regulatory rather than commercial.

  • Regulatory writing and submissions
  • Pharmacovigilance case intake
  • Trial site operations, monitoring
  • Deviations, CAPA, quality events
  • Medical information response

Buyers: pharma, biotech, CROs, CDMOs

Medical technology

Post-market and commercial operations at device companies, where volume grows faster than the team handling it.

  • Complaint handling, post-market surveillance
  • Quality management systems
  • Field service and dispatch
  • Reimbursement and coverage support
  • Sales operations and tenders

Buyers: device manufacturers, diagnostics, distributors

Platform layer

Enterprise agentic infrastructure

The layer that makes an agent something a regulated enterprise is allowed to deploy: orchestration across systems of record, permissions that follow a real identity, evaluation and monitoring that hold up in a review, and human checkpoints that are designed in rather than bolted on. Sector-agnostic by construction, but proven fastest where the stakes are highest.

  • Orchestration and workflow state
  • Identity, permissions, delegation
  • Evals, observability, drift detection
  • Guardrails and policy enforcement
  • Audit trail and validation tooling
  • Integration with EHR, ERP, LIMS, QMS

Criteria

What to send us

This is the whole filter. If it clears, send it. If it does not, send it anyway with one line on why it should be an exception.

The company

  • StagePre-seed through Series B
  • Check$100K – $1M; lead or follow
  • TractionAt least one customer paying real money outside a pilot
  • TeamSomeone on the founding team has worked inside the buyer's operation
  • GeographyUS and EU go-to-market; team location flexible
  • RoundPriced or SAFE; we are comfortable being the first institutional check

The product

  • AutonomyThe agent completes a task end to end. A copilot that only drafts is not what we are looking for.
  • RecordEvery action is logged, attributable, and reconstructable after the fact
  • EscalationA defined path to a named human, designed in from the start
  • BudgetSold against an operating line, not an innovation line
  • EvidenceMeasured reduction in cycle time or staff hours, not a demo
  • We pass onConsumer apps, general chat wrappers with no workflow, foundation model training, pre-clinical therapeutics, crypto-adjacent health

How we work

Fast answers, including the no

Step one · 3 business days

First read

Send the deck or a short email. You get a yes, a no, or one specific question. No NDA required to read a teaser.

Step two · 1 week

Terms

If it clears, we come back with a number and a structure before we start spending your time on diligence.

Step three · 2 – 4 weeks

Diligence

Customer calls, unit economics, security and compliance posture, and a real look at your evals and failure modes.

Step four

Close

We tell you at first read whether the capital is committed or whether we need a partner. We do not renegotiate without a written reason.

Contact

Send a deal

Founders can skip the warm intro. A short email describing what the agent replaces, and who currently does that work, is enough to get a real answer. It goes straight to a partner, not to a queue.

paul@parknovaventures.com

ParkNova Ventures LLC

Include if you have it

  • What the agent does, start to finish
  • Who did that work before, and how long it took
  • Current ARR and named customers
  • How escalation and audit are handled
  • Eval results and known failure modes
  • Round size, structure, and timing