See usage by team, project, and user
Track requests, tokens, models, and API keys per team, user, or project.
LLM Observability: Get the full picture of AI usage
Gain complete visibility into how AI is used across your organization – from shadow tools and prompts to Gateway-level traffic, performance & spend.
Chosen by leading engineering teams
🔥 Observer
One place to see and control AI usage
From ChatGPT in the browser to Cursor and Claude Code on the desktop, all tracked.
Tools outside your approved list, flagged and ranked by risk.
Which teams use AI most, what it costs, and the ROI you're getting
Sensitive data, blocked before it leaves your business.
No setup or disruption for your team, just instant visibility into AI usage.
🔥 Observer
Explore the platform
Observer
General
AI Visibility
Data Protection
Financials
Organisation
Your workspace, the devices it licenses, and who can reach the console.
AI GATEWAY
Observe and manage LLM requests
NexEco AI gives you one place to monitor how AI is being used so you can optimize model choices, caching habits, spend controls, and more.
Track performance and routing efficiency
Monitor latency, errors, and throughput across models and providers.
Monitor token usage and costs
Break down spend by model, application, project, team, user, API key, and individual request.
Investigate any request
Use logs and traces to see tokens, latency, routing decisions, cache behavior, costs, and errors behind any request.
Business benefits of
AI observability
AI observability isn’t just for technical teams. It’s a business-critical layer that gives security, finance, and visibility into how AI is used, what it costs, and where issues or risks emerge.
Reduce risk exposure
Spot policy violations, unusual usage, and potential risks with visibility into AI activity across your organization.
Control costs across your stack
See exactly what AI is costing you, by team, tool, and project, and cut unnecessary spend wherever it happens.
Prove compliance, build trust
Show stakeholders and regulators how AI is being used, and what protections are in place. Logs and reports make your policies verifiable, not just theoretical.
Prove AI adoption and ROI
See which teams are actually using AI day to day, not just who has a license, so you can prove your rollout is working.
What happens without full AI observability
When you can’t see how AI is being used, you can’t control the risks it creates. Blind spots in your AI stack and infrastructure create serious LLM challenges — from data leaks to runaway costs: