Evidently Analysis: $15M Raised

AI-assisted clinical data intelligence for healthcare

Enhance clinical documentation accuracy and efficiency; Streamline patient data retrieval for providers; Improve quality of care through actionable insights; Support value-based care initiatives; Assist in denial appeals and CDI reviews.

Achieved a 31.7-point increase in Net EHR Experience Score; Trusted by major healthcare organizations; Built around HIPAA and SOC 2 Type II compliance.

Evidently employs a hybrid go-to-market (GTM) strategy that combines elements of both product-led growth (PLG) and sales-led approaches. The website emphasizes integration with existing Electronic Health Record (EHR) systems, which facilitates easy access for healthcare organizations. However, there is no prominent option for a free trial or self-service signup, indicating a reliance on sales engagement. The absence of transparent pricing suggests that potential customers may need to contact sales for details, aligning more with a sales-led approach.

Customer testimonials highlight significant improvements, such as a "31.7-point increase in Net EHR Experience Score" and a "6x return on investment" for clients, indicating a structured sales cycle rather than viral adoption. While educational resources are available, they focus on showcasing the product's benefits rather than extensive self-service learning materials. This suggests a strategy that leans towards high-touch relationships with healthcare organizations, optimizing for larger contract values and executive buy-in rather than rapid user adoption.

Evidently has reported notable clients on their website, including:

1. University of Iowa Health Care: They integrated Evidently's clinical data intelligence, resulting in a significant 31.7-point increase in their Net EHR Experience Score.
2. Allina Health: This client achieved a 6x return on investment through the use of Evidently for value-based care risk adjustment and revenue capture.

The nature of the relationships involves Evidently providing AI-assisted tools that enhance clinical workflows and improve patient care quality, demonstrating tangible benefits in both user experience and financial performance.

Evidently employs a diverse technology stack primarily focused on data and cloud infrastructure. The programming languages prominently used include Python, SQL, and Bash scripting, with frameworks like Django and FastAPI supporting their development efforts. Their infrastructure is heavily based on Google Cloud Platform, utilizing tools such as Kubernetes and Cloud SQL for deployment and management. Data technologies include PostgreSQL and BigQuery, indicating a strong focus on data processing and analytics. However, there was no information found regarding sales or marketing technologies.