Narus AI
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Secure platform for managing Generative AI effectively.
Narus AI Product Information
Narus | AI Chat for Businesses is a secure, enterprise-ready GenAI chat platform designed to give teams access to powerful AI models without compromising data security or incurring uncontrolled costs. It provides real-time usage and cost visibility, strong data governance, and integrations with multiple LLMs (e.g., GPT-4o, Claude, Gemini) through APIs, all in a private, policy-driven environment. Narus is positioned as a trusted solution for security-focused businesses to adopt GenAI confidently, avoid shadow AI, and scale AI initiatives responsibly.
Overview
- A secure GenAI chat portal for organizations to enable productive AI-assisted workflows while preserving data privacy and security.
- Visualizes usage and estimated costs in real time to help governance, budgeting, and optimization.
- Connects to multiple LLMs via APIs with granular access controls, enabling teams to choose the right model for the right task.
- Emphasizes data protection: company data is never used to train public models; data storage and handling are managed to meet security standards.
How Narus Works
- Connect to your preferred LLMs (e.g., GPT-4o, Claude, Gemini) using API keys.
- Configure granular access permissions for teams and users to control who can run which models and tasks.
- Interact with GenAI in a secure environment where all AI interactions are private and data is segregated.
- Monitor usage and costs in real time to optimize adoption and avoid overspend.
Narus stores data on a dedicated AWS instance managed by Kolekti (part of The Adaptavist Group) with robust encryption and data segregation to protect sensitive information. Your data is not used to train public models unless you opt in.
Use Cases
- Enterprise productivity: accelerate drafting, ideation, and analysis with secure AI assistance.
- Governance and compliance: controlled access, auditing, and cost visibility to align with corporate policies.
- AI strategy and adoption: insights into adoption trends and high-value use cases to maximize ROI.
Security & Compliance
- Private, restricted environment for all AI interactions.
- Data never used for public model training by default.
- Dedicated AWS storage with encryption and strict data segregation.
- Administrative controls, budget management, and monitoring to prevent data leakage and uncontrolled spend.
How to Get Started
- Book a 1:1 demo to explore use cases, governance, and integration options.
- Connect your preferred LLMs via API keys and set up access controls for teams.
- Begin using Narus in a secure, compliant manner while monitoring costs in real time.
Pricing & Costs
- Cost is driven by token usage for each LLM; Narus provides an estimated cost based on tokens used in inputs and outputs.
- LLM provider bills for actual tokens; differences between Narus estimates and provider invoices can occur.
- Detailed pricing guidance and integrations information are available in the product resources.
FAQ Highlights
- What is Narus? A generative AI chat portal for businesses with administrative controls, budget management, and usage oversight.
- Who is Narus for? Organizations seeking AI benefits with strong security and governance.
- Is data used for model training? No, by default; data is not used to train public models. Opt-in training is model-dependent.
- How are LLMs connected? Through API keys; see integrations page for compatible models.
- How are costs calculated? By token usage; Narus provides estimates and decouples from provider billing.
Core Features
- Secure, private GenAI chat environment for businesses
- Real-time usage and cost visibility for governance and budgeting
- Multi-LLM access with granular user and team permissions
- Data privacy: company data not used for public model training by default
- Dedicated AWS storage with robust encryption and data segregation
- Administrative controls for AI usage, costs, and policy enforcement
- Easy integration with existing workflows and enterprise systems
- No vendor lock-in with flexible model selection