For managed security providers
Run the first look for every customer you serve from one platform, with each customer’s people, connections, settings and records kept apart from every other customer’s.
A provider’s analysts switch between customers all day, and every switch costs time and attention.
Each new contract brings its own alert queue. If each alert needs an analyst’s first look, growth means hiring at the same pace, and margins shrink with every customer you win.
Which machine runs payments at one customer and which account is a service account at another: analysts carry this for dozens of environments, and mix-ups are easy to make.
Customers expect their data to stay theirs. You need to show that one customer’s alerts, people and settings never mix with another’s, and that every action is on record.
Turning an investigation into something a customer’s manager can read is slow, careful writing. It is often done late, after the technical work is finished and the next alert is waiting.
Different tools, models and people per customer, on one platform.
Each customer is its own tenant, with its own people, connections, settings, usage limits and audit trail. Your analysts work across the customers they are allowed to see, and nothing from one tenant appears in another. Adding a customer means adding a tenant, not another system to run.
New alerts from each customer are collected automatically and given a verdict, real attacks first. Your analysts start from the agent’s conclusions and the evidence behind them, and spend their attention on the alerts that need a person rather than on the routine checks that come before.
Alerts that belong to the same attack are joined into one campaign, with its stages from first to last, the machines and accounts it touched and the business processes it puts at risk. In our lab, twelve alerts from five rules became one attack, from discovery to collection.
Which AI model a customer uses, whether anything may be sent outside its environment and how much it may use are set customer by customer. A customer who needs everything kept on its own hardware can have that, while another is hosted for them.
Investigations can be shared as reports in HTML, Word or PDF, written for the people who receive them. A customer’s manager gets a plain account of what happened and what is recommended, with the evidence there for their own technical staff to follow.
Each new customer becomes a tenant with its own people, connections, settings, AI model choice, usage limits and audit trail, on the platform you already run.
Connect that customer’s Elastic Security, Splunk, Microsoft Sentinel, CrowdStrike Falcon or Microsoft Defender, and record their important systems, business processes and urgent contacts.
New alerts from each customer are investigated inside that customer’s tenant, using only its own data, its own context and the corrections remembered for it.
Your analysts check verdicts for the customers they may see, approve plan steps and share plain reports with each customer, built only from that customer’s data.
People, connections, settings and records kept separate for each customer you serve, on one platform you run once.
Each customer’s important systems, business processes and urgent contacts, used in every verdict and campaign for that customer.
Corrections your analysts make are remembered for later investigations about the same customer, and never carried over to another.
Set how much each customer may use, so one busy environment does not crowd out the others.
Who approved what and when, kept separately for each customer and ready to show them when they ask.
Each customer’s findings go to the Slack, Teams, PagerDuty, email or ticket queue set for that customer.
Each customer is a separate tenant with its own people, connections, settings, AI model choice, usage limits and audit trail. Investigations for one customer read only that customer’s connected tools, and what your analysts teach the agent about one customer is remembered for that customer alone.
Your own staff can be given access to the customers they work on, and each customer’s people see only their own tenant.
Yes. Connections are set per tenant, so one customer can run Elastic Security while another runs Splunk or Microsoft Sentinel, alongside CrowdStrike Falcon or Microsoft Defender. Elastic is the deepest connection today: coverage checks and adding log collection through Elastic Fleet are Elastic features.
Notifications and tickets are set per customer too, so findings go to the channel or queue each customer expects.
Yes. armor360 can run fully on-premises, the AI included, on the customer’s own hardware, so alert data need not leave its environment. External AI fallback can be switched off. Other customers can be hosted, and the choice of model is set customer by customer.
That lets you serve customers with strict data rules and customers who want a hosted service from the same platform, without running two products.
No. It detects, investigates and recommends. Your analysts, or the customer’s own people, decide and act. When an attack needs a coordinated plan across several machines and accounts, every step waits for a person’s approval, and the approval is recorded in that customer’s audit trail. Decisions about each customer’s systems stay with the people your contract says should make them.
Pricing is by quote, sized to what you protect across your customers, with no charge per person. Adding analysts or customer users does not add to the bill. As a guide to running cost, an investigation uses about $0.10 of compute; that is an estimate of cost, not a price. Tell us how many customers and machines you look after and we will size a quote.
Start a free pilot on your own alerts, or put in your own numbers first.
