Questions about DataLily AI

DataLily AI is a market intelligence platform for US healthcare. It brings negotiated rates, reimbursement, procedure volumes, referral networks, ownership and coverage rules into one view, so teams can size a market, compare rates or vet a target with confidence. Every figure is dated and labeled by how certain it is.

DataLily AI is built for pharma, medtech, RCM firms, private equity, surgery centers, lenders, TPAs and employee benefits teams. They use it to evaluate commercial negotiated rates, benchmark reimbursement, assess procedure volumes and referral networks, and track facility ownership and clinical coverage rules across US markets.

Commercial negotiated rates are the prices private health plans agree to pay providers for specific services. DataLily AI lets teams compare them across payers, plans, services and markets. They reflect contract terms, not paid amounts.

Every figure in DataLily AI shows when it was last updated and whether it is labeled fact, signal or estimate, so teams know how much weight to give it. Rates are shown as contract terms, not paid amounts, and gaps are flagged rather than filled with guesses.

Compare your rates with similar providers in the same market. DataLily AI shows where your rates sit against comparable peers, payer by payer and service by service, and highlights the payers where you are furthest behind, so your next renewal starts from evidence.

Reference-based pricing lets self-funded health plans pay providers a set percentage of a benchmark, usually Medicare, instead of a network rate. DataLily AI gives TPAs and employee benefits teams the market rate context to set and defend those percentages.

DataLily AI ranks clinicians, practices and facilities by volume for a procedure in any US market and shows how that volume splits across care settings. Volume figures cover a defined patient population, not all payers, and each one carries its as-of date.

Not directly. DataLily AI maps referral networks: which physician groups are aligned with which health systems, and when a group moves to a competitor. It does not track individual patient flows.

DataLily AI maps owners, parent companies and minority stakes for hospitals, surgery centers and physician practices, each with an as-of date. Where ownership cannot be confirmed, it is flagged as a gap rather than assumed to be independent.

Each payer sets its own criteria, so prior authorization, step therapy and site-of-care requirements can differ for the same drug or procedure. DataLily AI tracks those requirements across payers and shows when each one changed. It reports the rules, not approval rates.

Lenders and private equity teams use DataLily AI to check a target’s ownership, rate position, procedure volumes and physician alignment before a deal, with every figure dated. It shows what can be established up front and what still needs confirming with the target.

Payer rate benchmarking compares what one insurer pays a provider for a service with what similar providers in the same market are paid. DataLily AI does this by payer and by service, highlights the payers where a provider is furthest behind, and dates every figure, so contract renewals start from evidence instead of guesswork.

DataLily AI covers every US market, from major metros to rural counties, and the full range of providers: hospitals, surgery centers, physician groups, imaging and infusion sites. Coverage is deepest for procedure-heavy specialties such as orthopedics, cardiology, gastroenterology, ophthalmology and oncology, and expands as new records are added.

Most healthcare data tools are built for one industry, so they only show changes in that market. DataLily AI connects all of US healthcare, so you see your market plus the changes elsewhere that affect it: a new insurer rule, a surgeon changing groups or a change in ownership.

No. DataLily AI needs no connection to your EHR, billing or scheduling systems and no IT project. Share the market, contract or target you are working on, and your team gets a sourced analysis to review.

No. DataLily AI shows what the evidence supports today, with each figure dated and labeled. Forecasting will be offered only once it has been tested against real outcomes.