Prior authorization & UM · Payer rules & ePA automation
Itiliti Health
Itiliti Health automates prior authorization by exposing payer medical policies and driving electronic PA workflows for plans and providers. It is PA interoperability software, not a core claims system.
Strong fit
- Health plans preparing for electronic prior auth mandates that need payer-rule transparency for providers
- UM leaders who want automation against published medical policies rather than only more nurse reviewers
- Buyers comparing mid-market PA interoperability platforms ahead of CMS-0057 timelines
Weak fit
- Solo clinics that only need a fax-replacement PA form filler
- Plans already locked into a single incumbent UM suite with no budget for another layer
- Buyers that need imaging AI rather than authorization workflow
Bottom line
Itiliti Health earns a Recommend on the plan-side of our prior authorization board. Founded by Michael Lunzer and led by CEO Kevin Aniskovich, the Eden Prairie company automates prior auth by exposing payer rules and driving touchless electronic workflows for plans and providers. Third-party estimates put revenue near $1-3M with a small team after early venture rounds, inside the prefer band and earlier-stage than Agadia or Xsolis. Implementation is a UM policy and interoperability project. Pricing is enterprise SaaS. Score sits with Silna on focused PA automation and below Xsolis on AI utilization prediction maturity.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Itiliti Health is an Eden Prairie prior authorization company founded by Michael Lunzer and led by CEO Kevin Aniskovich. Plans and providers use it to communicate payer medical policies clearly and automate electronic prior authorization instead of relying only on portals and faxes.
It is PA interoperability software, not a full core claims system and not imaging AI. Compare Agadia when you need a mature PBM/health-plan PAHub suite, Banjo Health when plan-side AI criteria composers are the frame, and Xsolis when AI utilization prediction is the center of the buy.
Score reflects focused ePA automation with earlier commercial scale than the largest UM incumbents.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Xsolis | 7.8 | 7.3 |
| Infinitus | 7.7 | 7.4 |
| Agadia | 7.6 | 7.2 |
| Careviso | 7.6 | 7.3 |
| Silna Health | 7.3 | 7.1 |
| Itiliti Health | 7.3 | 7.1 |
| Banjo Health | 7.2 | 7.0 |
| Hindsait | 7.0 | 6.7 |
| Rhyme | 6.5 | 6.3 |
Pricing
| Item | Detail |
|---|---|
| Model | Enterprise SaaS for prior authorization automation; quote-based for plans and partners. |
| What usually drives cost | Authorization volume, lines of business, policy coverage, and integration scope. |
| What to ask in diligence | Annual platform fee at your PA volume, including policy configuration and training. |
| Published pricing | No public list price. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Itiliti Health to function | |
| UM or PA owner named | Policy projects stall without owners. |
| Medical policies scoped for automation | Vague rule sets produce junk decisions. |
| Baseline PA turnaround metrics | You cannot prove lift without a baseline. |
| Payer/provider integration path clear | ePA dies on connectivity. |
| Appeals path documented | Automation still needs human override. |
| What will maximize your value | |
| Pilot one line of business first | Enterprise day-one multiplies noise. |
| Measure touchless rate at 90 days | Prove PA automation. |
| Retire overlapping portal bots | Duplicate PA queues confuse staff. |
| Deal-breakers | |
| Fax form-filler only | |
| No policy sharing allowed | |
| No UM owners | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Policy and security mapping | 4-8 weeks |
| 2 | Pilot LOB | 6-12 weeks |
| 3 | Scale ePA | 4-8 weeks |
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 actually 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.