What is Nightfall?
- Model and environment constraint resolution
- Safe rollbacks and recalls
- Staged upgrade and rollout strategies
- Configuration management
- Proactive monitoring and alerting
- Compliance and auditability
- Security operations [SecOps]
- Software supply chain
- Multi-cloud
- On-premise
- Private SaaS
- Regulated
- Edge
Nightfall releases your AI, keeps it running, and fixes it when it breaks, in every environment you run.
- Within hours of connecting it you can see everything you have deployed and how it is doing. From then on, a change your team makes reaches the live operation without a hand-built pipeline in between.
Nightfall Modules
Nightfall shows you everything you have deployed and lets you control it, so you can trust your AI in production.
A live picture of your landscape, from the Nightfall Discovery Agent
- Within hours you see which models and services run where, at which versions, and whether they are healthy and ready.
Every release in one catalogue
- A live inventory of every model, service and configuration available to your environments, with its metadata, its origin and its latest releases.
Deliver new capabilities to every environment from the Control Center
- See what is happening across all your environments: detailed health, every rollout as it runs, and install, upgrade or roll back at the click of a button.
Run Anywhere.
One control centre, every environment you run.
Nightfall fits the way your engineering and operations teams already work, whatever mix of clouds, servers and sites they run.
Nightfall runs on:
- Public clouds
- Your own servers
- Customer-managed environments
- Sites with no internet
- Edge devices
Works with the tools your team already uses.
Nightfall plugs into your existing build and security tools, so your team ships faster instead of replacing what already works.
It sits above your infrastructure, not inside it, and you use only the parts you need.
It picks up where your build system stops: once a change is built, Nightfall takes it to every public, private and edge location you run, and keeps it healthy there.
Exceed Industry Benchmarks
| Workflow — AI deployment pipeline | Nightfall @ NRY | High | Medium | Low |
|---|---|---|---|---|
Deployment frequency For the primary system you work on, how often does your organisation deploy code or models to production, or release them to end users? | Hundreds of deploys per day 4,000+ / week | On-demand Multiple / day | Once / week To once per month | Once / month To once per 6 months |
Lead time for changes For the primary system you work on, how long does it take to go from code committed to code running successfully in production? | 6 Minutes | One day to one week | One week to one month | One month to six months |
Time to restore service When an incident or defect impacts users, such as an unplanned outage or a service impairment, how long does it generally take to restore service? | 9 Minutes | Under one day | One day to one week | One week to one month |
Change failure rate What percentage of changes to production result in degraded service and subsequently require remediation, such as a hotfix, a rollback, or a fix-forward patch? | 3.8% | 0% – 15% | 16% – 30% | 46% – 60% |
Industry bands follow the DORA State of DevOps benchmarks; Nightfall figures are notional.