AI agents that eliminate work
Candid AgentKits combine rules, agents, and insights to resolve and prevent issues in your existing billing system.
AgentKits are built to lower your costs, not profit from your issues
Lower costs permanently by preventing issues
Agent-only approaches only work denials after they happen. Since they bill per task, more denials means more revenue. AgentKits trace each issue to its root cause and add upstream rules to stop it from recurring, helping you minimize rework costs, delayed cash, and patient friction.
Use rules to avoid wasteful token spend
Agent-only approaches throw agents at every task, even ones rules could handle with no token spend. Each AgentKit codifies your processes and payer logic into rules and saves agents for complex work. As it surfaces new rules from claims and agent actions, more work shifts to rules and costs keep falling.
Automatically investigate, resolve, and prevent denials
The Denials AgentKit investigates root cause with payer calls and portal checks, prepares appeals, handles write-offs, and routes exceptions to billers. It detects broader denial trends and automatically suggests claim edit and validation rules to stop future denials at the source.
Catch coverage issues before they cost you
The Eligibility AgentKit verifies coverage before care, generates patient estimates, and handles exceptions with payer calls, policy analysis, and plan carve-out identification. It suggests rules from recurring issues and flags them at scheduling, so fewer claims are denied.
AgentKits route each issue to the most reliable, cost-efficient tool
AgentKits integrate with EHR, clearinghouse, and other tools and create a unified data model so agents have all the relevant information for each claim.
Rules codify your processes alongside payer logic reverse-engineered by Candid. They instantly resolve issues that fit known criteria without wasting tokens.
Agents handle complex tasks, like payer calls, portal checks, and policy analysis. Since healthcare data can be messy, agents cross-check multiple sources before drawing conclusions.
True exceptions go to your billers in their existing billing tool. They approve an agent's proposed fix or take action themselves.
AgentKits use LLM and ML techniques to analyze claim history and agent actions to suggest new preventative rules. Learnings from one AgentKit carry over to another.
Audit logs and activity history show what action was taken and why, whether by an agent or a rule. Every rule change is versioned and logged.
Collect more without changing your billing system
See how AgentKits resolve and prevent issues without replacing the tools your team already uses.