Revenue cycle · Denials & AR automation
Janus Health
Janus Health makes JanusIQ, software that automates claim status checks, payer website lookups, prior authorization, and referral intake for hospital revenue cycle teams and shows leaders how staff spend their time.
Strong fit
- Health systems on Epic with large claim follow-up and prior authorization teams
- Revenue cycle leaders who want to see how each team member spends time on claims
- Teams that spend hours checking claim status on payer websites
Weak fit
- Physician practices and small groups
- Buyers who want published outcome studies from customers they can identify
- Buyers who need a published price list
Bottom line
Janus Health makes JanusIQ, software for hospital revenue cycle teams that automates claim status checks, payer website lookups, prior authorization, and faxed referrals, and shows leaders how their staff spend time. It fits health systems that want to get more done with the billing staff they have.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Brendan Downing, who had worked as a revenue cycle project manager at Epic, co-founded Janus Health in 2020. Janus builds automation for hospital billing staff.
Teleport, a tool for getting around payer websites, saves staff up to five hours of manual lookup a day, Janus says. Claim Intelligence checks claim status on payer sites and writes the result back to the EHR. Its referral tool turns faxed referrals into orders in Epic.
In June 2025 it combined these tools as JanusIQ, with three parts. AccessIQ handles front-end work, AccelerateIQ handles claims, and AdaptiveIQ shows leaders how each person works and where processes slow down.
Caduceus Capital Partners co-led its $8.8 million Series A in 2022. Enhanced Healthcare Partners made a growth investment in March 2023 and led a $10 million Series B extension in October 2024.
Todd Doze became chief executive in May 2024, and Downing stayed on the board. Janus says health systems using it collect up to 2% more of what they are owed and get paid five days sooner.
Adonis fits a health system that wants denial analytics with AI agents. SuperDial fits when payer phone calls are the main burden.
Sift Healthcare fits when clinical denials should be predicted before claims go out. Enter Health fits a group that wants AI across the billing cycle.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Adonis | 7.8 | 7.6 |
| Enter Health | 7.3 | 7.0 |
| SuperDial | 7.2 | 7.0 |
| Sift Healthcare | 7.1 | 6.8 |
| MD Clarity | 6.9 | 6.7 |
| Janus Health | 6.9 | 6.9 |
Pricing
| Item | Detail |
|---|---|
| Model | A custom contract quoted by Janus Health. |
| What usually drives cost | The number of users and hospitals, which tools you use (prior authorization, referral intake, claim status, payer website lookups, staff analytics), and EHR connection. |
| What to ask before you buy | Whether you pay per user or per transaction, setup fees, and references from health systems of your size. |
| Published pricing | Janus Health does not publish a price list. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Janus Health to function | |
| A billing leader who owns claim follow-up | It changes how the team spends its day. |
| Access to Epic or another EHR | Results are written back to it. |
| Payer portal credentials | The automation logs in for staff. |
| Starting claims worked per person | You need them to show the change later. |
| Staff to check the automation's results | This builds trust early. |
| What will maximize your value | |
| Start with claim status checks | It is high volume and low risk. |
| Use staff work data in coaching | This shows what works best. |
| Use the time saved on complex claims | This recovers more money. |
| Deal-breakers | |
| You are a small practice | |
| It cannot write results back to your EHR | |
| No one owns follow-up | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Contract and EHR connection | 1-3 months |
| 2 | First automations live | 2-4 months |
| 3 | More tools and teams | 6-12 months |
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.