Provider credentialing & network · AI credentialing & enrollment
Assured
Assured uses AI agents to automate provider credentialing, payer enrollment, and related network operations. It is not an EHR or staffing marketplace.
Strong fit
- Provider groups and digital health companies that need AI agents for credentialing and payer enrollment
- Network teams that track how many days it takes from application to being in network
- Buyers that want automated credential checks built around NCQA standards, without building a large verification team in-house
Weak fit
- Buyers that require a decade of public financial history before a pilot
- Organizations that only want exclusion list monitoring, without enrollment
- Clinics looking for a telehealth prescribing network
Bottom line
Assured is worth considering for provider groups and digital health networks that want AI agents to handle credentialing and payer enrollment. It suits teams with a credentialing owner and clean provider applications. Buyers who want a more established vendor may prefer CertifyOS or Medallion.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Assured automates provider credentialing, payer enrollment, licensing, and related network work with AI agents. Varun Krishnamurthy is CEO, and in July 2026 the company raised a $19 million Series A led by Insight Partners. It is not a general HR onboarding tool.
Customers get providers in network sooner when the agents work through original sources and enrollment packets in place of spreadsheet queues.
Because the company is still growing, buyers should check its references and security reviews closely. Implementation needs someone to own credentialing and clean provider applications, and prices are quoted for each customer.
Among credentialing tools, Assured scores below CertifyOS and Medallion on maturity and above Modio and ProviderTrust on how much it aims to automate. The score reflects strong automation goals, held back until there is more public proof of results.
Other tools may fit better. CertifyOS suits a health plan that wants provider data through an API, and Medallion suits a growing group that mainly needs enrollment software. Verifiable suits a buyer that wants a credentials verification organization run with AI.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Medallion | 7.7 | 7.3 |
| CertifyOS | 7.7 | 7.4 |
| Andros | 7.6 | 7.3 |
| Assured | 7.4 | 7.2 |
| Credentially | 7.2 | 7.0 |
| Verifiable | 7.1 | 6.9 |
| Welter Healthcare Partners | 7.0 | 7.2 |
| Incredable | 6.8 | 6.6 |
| Modio Health | 6.8 | 6.8 |
| ProviderTrust | 6.8 | 6.6 |
| Medversant | 6.7 | 6.4 |
Pricing
| Item | Detail |
|---|---|
| Model | An AI platform for credentialing and enrollment. Prices are quoted for each customer. |
| What usually drives cost | How many providers you add, how complex enrollment is, how much verification work Assured does, and support. |
| What to ask before you buy | The yearly or per-provider cost at your volume of new providers, with turnaround guarantees and audit records spelled out. |
| Published pricing | Assured does not publish prices. Expect packages based on your number of providers. |
Prerequisites for purchase
| Need | Why it matters |
|---|---|
| What you need to get Assured to function | |
| A named owner for credentialing or network operations | Software with no owner goes unused. |
| Current numbers for days to onboard and for errors in applications | Without a starting number, you cannot prove the value. |
| A written list of the sources for licenses, CAQH, and payer portals | Missing sources send staff back to chasing documents by hand. |
| A plan for who handles incomplete applications after launch | Incomplete files that no one works on never get enrolled. |
| NCQA or payer audit expectations written down | Unexpected audit rules wipe out the gains. |
| What will maximize your value | |
| Track the median days to get in network every week for 90 days | Logins to the portal are not results. |
| Start with one specialty or line of business first | A small real win is worth more than a broad launch with nothing behind it. |
| Drop the old tracking spreadsheets after one month of running both | Entering everything twice doubles the cost. |
| Review stuck applications at a regular team meeting | Applications that quietly sit hide problems. |
| Send growth leaders a monthly update on network operations | Enrollment delays no one hears about lead to unexpected drops in income. |
| Deal-breakers | |
| Nobody will own incomplete credentialing files. | |
| You will not do the source checks or payer enrollment work the product needs. | |
| You expect an EHR replacement from a credentialing tool. | |
| Leadership will not measure onboarding turnaround. | |
| Your legal team will not sign the required data use agreements. | |
Value creation time frame
| # | Stage | Typical range |
|---|---|---|
| 1 | Plan and measure the starting point | 2-4 weeks. Agree on measures, data sources, and which lines of business are covered. |
| 2 | Set up | 4-12 weeks. Set up checks, workflows, and connections. |
| 3 | Pilot | 4-8 weeks. Run one specialty or region and audit a sample of files. |
| 4 | Expand | 2-4 months. Add lines of business and stop using side trackers. |
Leadership
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.