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Take action on your cloud & AI security.

Pleri is an agent that gives your security team 4x the output. She works out which risks across your cloud and AI workloads are actually exploitable, then fixes the ones that are and sees each change through to a merged PR.

4.7 on G2Top-rated cloud security platform

Animated demonstration of the Pleri AI security assessment terminal. Pleri runs an AI-SPM assessment across a GCP environment, scans Vertex AI, Model Armor, and Document AI resources, evaluates 14 posture checks across 3 projects, and reports findings including a critical Model Armor risk: prompt injection guardrail not enforced on publicly reachable LLM endpoints.

Punch above your headcount

Pleri is your AI security engineer. You bring her onto the team like a hire and point her at a real problem. She learns how your environment is built and fixes what's exploitable in it. Every change is yours to approve.

Try Pleri in your environment

Output4Xthe work of your current team

This is transformational for us. Pleri saves hours and hours of unproductive research during investigations. We’re seeing the equivalent of 2-3 full-time engineers worth of productivity gains. - Buildkite

How she works a finding

What Pleri does the moment a finding shows up, before it ever becomes your problem.

  1. Investigates the finding

    Pleri pulls the context a human would: what the resource is, who can reach it, what it connects to. No jumping between five consoles to assemble the picture.

  2. Checks whether it's real

    The finding gets run against your environment to see if it is actually exploitable. A critical CVE on something nothing can reach is not critical. This is where most of the backlog quietly disappears.

  3. Fixes it

    Pleri raises a PR with the change, files the Jira ticket, and pings the owner in Slack with the reasoning behind it. The fix is auto-generated. The merge is yours.

  4. Follows it through

    Pleri nudges the PR if it goes stale, confirms the bucket is closed once it is merged, and closes the ticket. Then it is on to the next thing worth doing.

Before

“We think our critical risks are covered.” Posture is a guess between scans. The board report takes a week and arrives wrapped in caveats.

With Pleri

“We know what is closed, what is in review, and what is blocked.” Every fix has an owner, a PR, and an audit trail behind it.

~90%:  of a typical backlog retired as non-exploitable

One finding, start to finish

The kind of finding that usually waits weeks for an owner. Here it is, in minutes.

Animated demonstration of a Pleri security response in Slack. In #security-team, Pleri finds a new public S3 bucket in a production account: internal-data-analytics-backup is public and holds PII. Pleri blocks public access as a stopgap, opens JST-78 as critical, and raises a PR to fix the Terraform behind it, with a View in Github action. Jeremy Kiel replies that the PR looks good and is approved. Pleri reacted with a chef's kiss. Pleri then confirms the merge is applied: the bucket is private again, JST-78 is closed, and the account remains monitored.

Purpose-built AI security, in the order that protects you.

  • AI asset inventory

    Every AI model, agent, and MCP server running across AWS, Azure, and GCP, including the ones nobody told security about. Exportable as an AI bill of materials when an auditor asks.

  • AI posture (AI-SPM)

    Checks the guardrails on your AI systems: logging switched off, training jobs running outside a private network, data left on default encryption. The same posture depth we run across the rest of your cloud, now on AI.

  • AI compliance

    Every AI finding maps to the standards your board and customers ask about. Open a control, see which findings put it at risk and which you already meet.

    • ISO/IEC 42001
    • OWASP LLM Top 10
    • NIST AI RMF
    • OWASP Agentic Top 10
    • MITRE ATLAS

  • Coming soon

    AI data security

    Watches the data behind your models, from training sets to the vector store, and flags sensitive information before it reaches a model or leaves one.

  • Coming soon

    AI agent security

    An agent that acts on its own is an identity to govern. Controls for what it can reach and what it’s allowed to do unattended, including agents connected over MCP.

  • Coming soon

    AI runtime visibility

    See an AI system in action, not just at rest. Captures each call and the data moving through it, and ties live activity back to your posture findings.

What our agent actually does

Five built-in skills, plus any workflow you teach her. Each one ends in a fix or a straight answer, not another dashboard.

  • Custom skills
  • Exploitability analysis
  • Cloud security
  • Code security
  • Compliance
AgentSkills

Custom skills

Teach her how your team works.

Beyond the built-in skills, you can hand the agent your own playbooks, so a process you would normally write up in a runbook runs the same way every time.

CONTROL: Personal or org-wide, with admins in control of what runs.

  • Build a skill from a prompt, import one from a file or repo, or install from the open Skill Library
  • Back a skill with scripts for deterministic output, so the numbers come from the script and not a guess
  • Built on the open AgentSkills standard, portable with tools like Claude Code
ExploitabilityVulnerability triage

Exploitability analysis

Most of your criticals are not.

Pleri checks each vulnerability against the asset it actually lives on. Is the service running? Is it reachable? Is the vulnerable feature even switched on? A CVE is not exploitable everywhere, and a base severity score rarely matches what the vulnerability means in your account.

Around 90% of a typical backlog is not exploitable. This is how teams get out of backlog prison without taking on more risk.

  • Sorts findings into not exploitable, likely not, likely exploitable, and unclear, with the evidence behind every call
  • Separates base severity from operational severity, the real risk on your asset in your environment
  • Ranks the fix by payoff: rebuild the image to clear hundreds of CVEs at once, patch the package, mitigate, or formally accept the risk
AWSAzureGCP

Cloud security

Find the misconfiguration and the path it opens.

Pleri reads misconfigurations, public exposure, and over-privileged access across your cloud accounts, and connects them, so a config gap and the identity that makes it reachable show up as one path instead of two unrelated alerts.

WHERE: She works inside the AWS console through the browser extension, where your team already is.

  • Surfaces public access, weak configs, and privilege-escalation paths across AWS, Azure, and GCP
  • Maps the blast radius so you see what a finding actually puts at risk
  • Files the ticket, raises the fix, and walks the team through console changes when there is no PR to raise
IaCSCASecrets

Code security

Catch it in the repo, not in production.

Pleri scans your repositories for infrastructure-as-code misconfigurations, exposed secrets, application security issues and vulnerable dependencies, then raises the PR to fix them and keeps the backlog of pull requests clean.

From finding to merged PR, with a human approving every change.

  • Scans GitHub and GitLab for Terraform and CloudFormation issues, hardcoded secrets, and risky dependencies
  • Raises pull requests with the fix, requests review, and nudges the PR when it goes stale
SOC 2ISO 27001CISNIST

Compliance

Trace the failed control to the thing that broke it.

Pleri maps your findings to every framework in the catalog, then connects a failing control back to the code or cloud change behind it, so a failed control arrives with the fix that clears it.

The board report goes from a week of work to a question you can answer on the spot.

  • Checks alignment to SOC 2, ISO 27001, CIS, NIST, and custom frameworks as your cloud changes
  • Connects to Vanta and Drata
  • Produces an audit-ready report on request, instead of a week of gathering evidence

In the tools your team already uses

There is no new console to log into. Pleri shows up in the tools your team works in and acts there.

Access via

  • Slack
  • Microsoft TeamsTeams
  • Browser
  • MCP
  • CLI
  • Email
  • CI/CD
Pleri

Connects to

  • AWS consoleAWS
  • GitHub
  • GitLab
  • Jira
  • PagerDuty
  • ServiceNow
  • Vanta
  • Drata
  • +30 more

Teams that stopped managing the backlog and started clearing it

  • “We've moved from reactive to proactive.”

    From 30 days to 4 hours to fix

  • “It feels like a new AI security engineer, not a chatbot.”

    60% faster deployments

  • “Pleri saves serious headcount.”

    40 hours p/w saved on manual reviews

Powerful, never unilateral

Letting an agent make changes only works if you stay in control. You do.

  • Every change needs approval

    Pleri proposes the fix and raises the PR. Nothing merges until a human signs off on it.

  • Full audit trail

    Every action, recommendation, and decision is logged and reviewable.

  • One-click rollback

    Anything the agent does can be reversed.

  • Admin controls

    You decide what the agent can touch and what it cannot, per team.

  • Least privilege

    She only accesses what you have explicitly allowed, and you can revoke it instantly.

  • Runs on your terms

    Built on Amazon Bedrock with Claude. Your data never trains a model, and it stays in your region.

  • ISO 27001
  • SOC II Attested
View trust center

What teams ask before they start

Do I need security experience to use Pleri?

No. Pleri meets each person at their level and explains things in plain language, so an engineer who has never run a security review can hand her one and get a clear, actionable result.

How does Pleri decide what to work on first?

She won't flood you with alerts. Pleri weighs each finding against your actual environment and your business context, then surfaces only what's exploitable and worth acting on. The rest stays out of your way.

How fast can she be up and working?

She can be working in minutes. Connect Slack in two to three minutes, add the Chrome or Firefox extension in about thirty seconds, and hand her a task. Start with just Slack and add tools as you go.

Can my whole team work with her?

Yes. Pleri is built for teams: everyone can install the extension, shared Slack channels let her help several people at once, and role-based access controls who sees what.

Does Pleri train on our data?

No. Pleri runs on Amazon Bedrock inside AWS, and your data is never used to train or fine-tune a model. It's encrypted in transit and at rest, and every tenant is isolated.

Where does our data live?

Processing stays inside AWS, and you choose the region: Australia, India, Singapore, or the United States. Your data never leaves it.

Found it. Fixed it. Done.

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