Company
We build governed AI for the work enterprises actually run on
From AI Experiments to Operating Discipline
Most organizations have already tested AI. The hard part is making it useful inside regulated, data-heavy, cross-functional operations.
Performance AI helps companies move from isolated AI tools to governed AI workflows that work across documents, spreadsheets, email, databases, applications, reports, approvals, and daily operating decisions.
Edge gives executives, IT, compliance, and operators the controls they need: role-based access, approved sources, human review, source traceability, audit visibility, and measurable workflow outcomes.
Leadership
Our team combines enterprise technology, operations, healthcare, data, and go-to-market experience. We focus on the practical work required to make AI useful in complex organizations: workflow design, system integration, data readiness, governance, adoption, and measurable performance.
Dip Majumder is the Founder and CEO of Performance AI, which builds Edge, a governed AI execution platform for healthcare and other regulated and operationally complex industries. Performance AI focuses on a challenge many organizations encounter after successful AI pilots: moving AI beyond demonstrations and standalone copilots into secure, auditable workflows that produce measurable operational and economic results.
A computer scientist and technology executive, Dip has spent his career building and deploying technology in environments where reliability, security, and accountability are critical. Earlier in his career at AECOM, he helped build the mobile incident-management system used at Los Angeles International Airport, which received a Gold Medal in Security Technology Executive’s 2015 Security Innovation Awards. His background also includes Android platform engineering, enterprise systems, and large-scale operational technology.
Dip holds an MS in Computer Science from the University of Southern California and an MBA from the University of Chicago Booth School of Business. He was also selected as a Polsky Founders Fund Fellow at the University of Chicago.
Today, his work sits at the intersection of technology, operations, and economics: helping enterprises turn AI from experimentation into governed operating capacity embedded in the systems and workflows on which their businesses actually run.
Dip Majumder
Tina Djenge is the Co-Founder and Chief Operating Officer of Performance AI, where she focuses on turning emerging AI capabilities into practical business outcomes. Her work sits at the intersection of technology, operations, and commercialization—helping enterprises identify where AI can create measurable value and move from experimentation to adoption.
An engineer by training, Tina began her career working with international clients on refinery start-up operations and operational optimization. She later moved into technology product management, helping develop an early industrial IoT product, and at GE Transportation built AI and machine-learning optimization models for supply-chain operations. That progression—from complex physical operations to connected systems and AI—has shaped her approach to enterprise technology: innovation matters only when it improves how a business actually performs.
Over the course of her career, Tina has worked across Fortune 100 organizations, venture-backed technology companies, and entrepreneurial ventures, building and commercializing emerging technologies and translating them into growth, efficiency, and competitive advantage. At Performance AI, she brings that operating discipline to the challenge of helping regulated enterprises deploy AI in ways that are practical, governed, and tied to business priorities.
Tina holds a BS in Chemical Engineering from the University of Illinois Urbana-Champaign and an MBA from the University of Chicago Booth School of Business. Her work reflects a consistent theme across engineering, product, and entrepreneurship: bridging what technology makes possible with what organizations can successfully execute.
Tina Djenge
Compliance-Ready by Design
Designed for regulated environments with role-based access, connector governance, tenant isolation, source traceability, human review for sensitive actions, audit and activity logs, and customer-specific data controls. Compliance commitments, including HIPAA, SOC 2, ISO, or other frameworks, are governed by the applicable agreement, deployment scope, and security package.
Our Mission
Help regulated enterprises turn approved knowledge, systems, and workflows into governed AI-assisted work, improving operational performance without losing control of data, decisions, or accountability.
Our Vision
A future where AI safely becomes part of the operating capacity behind the workflows that run the business.
Our Purpose
Make AI practical, governed, and useful for teams doing complex work inside real enterprise systems.
Mission
Ready to Move AI Into Real Operations?
See how Edge turns approved company knowledge and connected systems into governed workflows your teams can use, review, and scale.
