Deploy secure, private AI assistants tailored to your enterprise needs. Nexa’s private assistant blueprint ensures control over data, advanced language capabilities, and seamless enterprise integration—empowering teams from operations to leadership
Data Sovereignty & Enterprise-Grade Control
Always-On, Context-Aware Assistance
Integrated with Internal Tools & Workflows
Private AI Assistants built on Nexa adapt to your organization’s unique workflows, offering tailored insights and responses that align with business context
Deploy assistants across teams and systems with enterprise-grade security, ensuring compliance while maintaining scalability for growing operations
Integrate effortlessly with existing platforms and tools, enabling smooth automation of cross-functional processes without disrupting current infrastructure
Empower teams with AI-driven recommendations and real-time insights, helping accelerate decision-making while preserving data privacy
Enables secure, one-on-one conversations through text, voice, or embedded interfaces. It adapts to user preferences, communication style, and task history—offering a personalized, responsive, and human-like assistant experience across devices
Maintains long-term user context, including goals, preferences, previous queries, and task states. This layer ensures continuity across sessions, allowing the assistant to recall past conversations and proactively assist in ongoing workflows
Executes tasks such as scheduling, email drafting, data lookup, and workflow triggering. This layer connects with enterprise systems, calendars, tools, and APIs to streamline actions with minimal user input
Runs AI models in a secure, isolated environment—on-device, edge, or within private cloud infrastructure. It ensures that sensitive data is never exposed externally, while still enabling advanced language understanding, summarization, and task execution
Implements role-based access, encryption, consent tracking, and data anonymization to maintain compliance with enterprise and regulatory requirements. This layer governs how data is processed, stored, and audited for full user control and trust
Acts as the intelligent control layer for AI assistants. It privately routes user requests based on context, policy, or fallback logic—ensuring secure, fast, and accurate interactions within enterprise boundaries
Optimizes inputs before reaching the LLM by structuring prompts with enterprise-specific data and logic—enhancing contextual accuracy, reducing hallucinations, and ensuring relevant outcomes
Provides real-time observability of assistant behavior, compliance, and responsiveness. Supports anomaly detection and lifecycle analytics to ensure trust and transparency
Offers granular insight into assistant interactions, surfacing patterns in user queries, response accuracy, and latency
Connects with private knowledge bases or vector stores to retrieve verified, organization-specific answers. Supports real-time access to FAQs, internal documents, or policy content—enhancing assistant reliability and trust
Protects internal APIs and resources with built-in access controls, rate limiting, and detailed request auditing. Ensures only authorized users interact with backend systems
Built using modern frontend frameworks like React or Angular and deployed within a secure internal network, it enables seamless access to dashboards and workflows
Built using modern frontend frameworks like React or Angular and deployed within a secure internal network, it enables seamless access to dashboards and workflows
Built using modern frontend frameworks like React or Angular and deployed within a secure internal network, it enables seamless access to dashboards and workflows
Built using modern frontend frameworks like React or Angular and deployed within a secure internal network, it enables seamless access to dashboards and workflows