Referral intake
Extract patient, payer, clinical, location, and order details and flag what is missing for human review.
We build internal AI products that organize referrals, eligibility and authorization, clinician matching, scheduling, documentation readiness, and care-team follow-up.
We begin with the operating reality, then design the product around the people, decisions, rules, and evidence already in the work.
Extract patient, payer, clinical, location, and order details and flag what is missing for human review.
Track required checks, documents, status, deadlines, and unresolved questions in one queue.
Match discipline, geography, availability, continuity, payer, and care requirements.
Surface incomplete records and follow-up needs before they delay care or downstream billing.
Not a standard product you have to work around. A focused operating layer that can connect the tools and data you already use.
Every referral, requirement, owner, status, and next action in one internal product.
Drafts follow-up, organizes handoffs, and escalates exceptions to the right person.
Supports assignment decisions while preserving clinical and operational oversight.
Checks completeness and timing against your rules before work falls through a gap.
These are study results, not forecasts for your business. We use them to establish plausibility, then model your ROI from your own volume, time, labor cost, error rate, and throughput.
Average result in a real-world deployment across 5,179 customer-support agents; less-experienced workers saw gains up to 34%.
NBER field study ↗A Harvard/BCG field experiment also found more than 40% higher quality on knowledge-work tasks inside the AI capability frontier.
Harvard Business School / BCG ↗Average firm-level effect in a 2026 BIS/EIB study of more than 12,000 non-financial firms adopting AI with complementary investment.
BIS / EIB study ↗We’ll show you the internal AI product that can simplify it.
Start the conversation →