A Single AI Platform To Support Your Enterprise

Aisera is the industry leader in Generative AI and has been the trusted partner for F1000 companies in their journey of AI and digital transformation with our enterprise-grade Universal Conversational AI Bots.

Our Generative AI bot delivers ChatGPT-like experience that can respond to user requests across multiple domains and in multiple languages with a true omnichannel experience. This results in a better user experience along with minimizing the deployment and maintenance costs across business functions like: information technology (IT), human resources (HR), customer service (CS), sales & marketing and contact centers.

Explore the extensive range of industry-specific skills and accomplishments Aisera has amassed throughout our collaborations with clients. Witness firsthand how our expertise in data science and Generative AI solutions can propel your business to new heights and accelerate growth.

Aisera is the leading provider of enterprise GPT generative AI solutions. Aisera’s mission is to help large, medium, and small enterprises to transform their business operating model with self-service by significantly reducing operational expenses, boosting revenue growth, and enabling human-like experiences. Aisera customers typically experience 75% or more automation in user requests and an 80% reduction in customer operations costs.

Aisera offers enterprise GPT generative AI solutions for IT, HR, Customer Service, Contact Center, Sales & Marketing and Finance departments. Its enterprise co-pilot supports multimodal user experiences (digital, voice, mobile, API) for AI & Automation.

The solution helps health systems to take a step-by-step approach to manage risk from population- to patient-level with easy to use dashboards powered by clinical and claims data. First, it helps understand the current state of risk management in the network with historical comparison to previous years risk scores. Second, it can answer “where to focus” by identifying the cohorts with the least risk recapture rates or maximum dropped/suspect codes, chronic disease distribution, month on month risk capture trend and more. Third, it helps prioritize patients with the largest number of coding gaps and get patient-level risk information to redirect resources strategically that reduces overall risk for the population.

Innovaccer is the data platform that accelerates care innovation through innovative AI technologies. Innovaccer’s AI-powered healthcare platform unifies patient data across systems and care settings, and empowers healthcare organizations with scalable, modern applications that improve clinical, financial, operational, and experiential outcomes. Innovaccer’s EHR-agnostic solutions have been deployed across more than 1,600 hospitals and clinics in the US, enabling care delivery transformation for more than 96,000 clinicians, and helping providers work collaboratively with payers and life sciences companies. Innovaccer has helped its customers unify health records for more than 54 million people and generate over $1.5 billion in cumulative cost savings. The Innovaccer platform is an industry-leading data and analytics platform, the Best in KLAS CRM solution, and the #1 rated population health technology platform by Black Book

Innovaccer's coder assistant identifies missing codes based on claims data and suggested clinical markers, helping avoid improper data submission and related consequences such as lengthy audits and repayments to CMS. The solution enables physicians and coders to save time by identifying information that could not be directly found in the patient's clinical or claims data. Failing audits, repayments to CMS, and legal ramifications are some of the unfortunate outcomes of improper data submission. Automation helps overcome these challenges by detecting suspect and dropped codes while reducing administrative burden.

Innovaccer’s risk management solutions support these efforts to help healthcare providers achieve their risk goals. The AI-powered coder assistant helps providers address coding challenges by analyzing dropped codes and reviewing claims data over multiple years to identify prospective coding opportunities and surface suspect codes based on evidence. This enables them to receive appropriate reimbursements by providing high-quality care to patients