Revenue cycle · Pharmacy and 340B automation
Plenful
Plenful is a San Francisco, California, company whose AI workflow automation platform handles pharmacy back-office work for health systems, including 340B program audits, intake and prior authorization, and reconciliation of Medicare drug price refunds.
Strong fit
- Health systems with 340B programs that want every claim audited
- Specialty and infusion pharmacy teams that want intake and prior authorization automated
- Pharmacy finance teams tracking Medicare Maximum Fair Price refunds
Weak fit
- Independent retail pharmacies outside health systems
- Physician practices whose main need is medical prior authorization
- Buyers who want a self-serve tool with a posted price
Bottom line
Plenful is AI automation built for health system pharmacy operations, from 340B audits to intake and Medicare drug refund tracking. It suits pharmacy, compliance, and finance teams buried in manual data entry and spreadsheet reconciliations. Independent pharmacies and practices that mainly need medical prior authorization should look elsewhere.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Plenful's customers are health system pharmacy departments, specialty and infusion pharmacies, and pharmacy companies such as Cencora. Pharmacy technicians, 340B compliance staff, and pharmacy finance teams use it to automate data entry, audits, and reconciliations that used to happen in spreadsheets. Its no-code software reads faxes, PDFs, spreadsheets, and electronic medical records, so it can work on top of systems a pharmacy already has. Plenful says it works with more than 95 health systems and pharmacy organizations.
Plenful sells enterprise contracts and does not publish prices. It has an estimated $25 million in annual revenue. For 340B work it competes with specialized 340B software and consultants. For intake and prior authorization it overlaps with Develop Health, Infinitus, and SamaCare, and TechCrunch listed Notable and Infinitus as competitors for health care automation.
Joy Liu founded Plenful in 2021 after working as director of strategic operations at Shields Health Solutions, a specialty pharmacy company now owned by Walgreens. Plenful came out of stealth in October 2023 with $9 million led by Bessemer Venture Partners, raised a $17 million Series A led by TQ Ventures in May 2024, and in April 2025 raised a $50 million Series B co-led by Mitchell Rales, co-founder of Danaher, and Arena Holdings, for $76 million in total. It has offices in San Francisco and New York City.
At the time of the Series B, Forbes reported 4x year-over-year revenue growth, and Liu said one health system found $1.2 million in additional 340B savings in its first two months on Plenful. Plenful says one 340B team went from spot-checking under 5% of claims to auditing all of them, and Fierce Healthcare reported its claim that the software cuts manual work by up to 97%.
In April 2026 Plenful launched MFP Intelligence, which tracks refunds health systems are owed under Medicare's Maximum Fair Price program for negotiated drugs, which started January 1, 2026. Plenful says customers including Henry Ford Health and St. Luke's Health System found up to 20% of expected refunds missing.
What customers say
What people like
"We went from spot-checking a small sample of 340B claims to auditing all of them, without adding staff."
"Our technicians stopped retyping referral faxes into the pharmacy system, and that time went back to patients."
What people don't like
"There is no rate card, so comparing it with other 340B tools meant a long pricing conversation."
"It is built around pharmacy, so our other departments still need separate automation tools."
Where customer reviews couldn't be found, our analysts attempted to give a voice to buyer sentiment, drawing on real information from review sites, forums, and product documentation.
Based on: Plenful Series B note, Fierce Healthcare, and Plenful company page.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Infinitus | 7.7 | 7.4 |
| Plenful | 7.6 | 7.6 |
| Notable | 7.5 | 7.0 |
| SamaCare | 7.1 | 7.0 |
| Develop Health | 7.0 | 6.8 |
Pricing
| Item | Detail |
|---|---|
| Model | Enterprise contracts with health systems, pharmacies, and pharmacy organizations. |
| What usually drives cost | The workflows automated (340B audits, intake and prior authorization, MFP reconciliation, rebates) and the number of pharmacies and sites. |
| What to ask before you buy | Ask Plenful how fees scale by workflow and site, and how savings found in audits are measured. |
| Published pricing | Not published. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Plenful to function | |
| Pharmacy and claims data access | Audits and reconciliations need the source files. |
| 340B or pharmacy ops owner | Sets rules and reviews findings. |
| IT sign-off on data feeds | Plenful runs on top of existing systems. |
| List of manual workflows | Picks the first use case. |
| What will maximize your value | |
| Start with 340B audits | Fastest dollar results. |
| Add intake automation next | Frees technician time. |
| Reconcile MFP refunds monthly | Catches missing refunds early. |
| Deal-breakers | |
| No access to pharmacy data | |
| Non-pharmacy automation needs | |
| Self-serve purchase required | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Data connection and configuration | 3-6 weeks |
| 2 | First workflow live | 1-3 months |
| 3 | Savings and hours measured | 3-6 months |
Leadership
Joy LiuFounder and CEO- Gurkanwal "GK" BrarChief Technology Officer
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.