Sikka offers Self‑Driving Practice (SDP), an AI‑driven platform that unifies scheduling, insurance, payments, reviews, and reporting into a single coordinated workflow for dental practices. Its DentalLLM and SAI agents generate actionable recommendations that can be simulated before live execution, with governed controls and real‑time performance metrics to improve production, collections, and patient experience across multiple locations.
Funding
Funding not disclosed
Founders
Product
Problem
Dental practices often rely on separate systems for scheduling, insurance, payments, reviews, and reporting, requiring manual follow‑up to reconcile recalls, balances, missing information, and claim exceptions. This fragmentation leads to inefficiencies, inconsistent execution across locations, and difficulty standardizing growth and patient experience.
Solution
Sikka’s Self‑Driving Practice (SDP) introduces an AI‑driven action layer that orchestrates workflows across all core dental operations. SAI agents and the DentalLLM analyze real‑time data to generate actionable recommendations, which can be previewed in simulation mode before live execution. Governed controls—including approvals, permission guardrails, audit logs, and a STOP function—ensure staff retain oversight while automation runs. Each automated action is tied to measurable goals such as schedule fill, production, collections, reviews, or team capacity, providing clear visibility into performance lift.
Target Audience
Primary customers are dental practice owners and administrators seeking to streamline operations, improve collection rates, and standardize patient experience across multiple locations.
Features
- Unified AI action layer that connects scheduling, insurance, payments, reviews, and reporting into a single coordinated workflow
- DentalLLM natural‑language engine that interprets practice data and suggests optimal next steps
- Recommendation mode with simulation preview to visualize outcomes before automation is applied
- Governed execution framework with approvals, permission guardrails, audit logs, and emergency STOP control
- Real‑time performance metrics linking every automated action to specific business goals (e.g., production, collections, schedule fill)
- Continuous learning loop that refines recommendations based on observed results and practice variations