Agentic SecOps that fit your stack.
Run AI operators directly from your existing data sources.
No new platform layer, no stack migration.
You want AI operations. You don't want to rebuild your stack to get them.
Most security products add AI on top of an existing stack of integrations, APIs, and one-off customizations — recreating the SOAR problem: capability bounded by your weakest integration, complexity that compounds every time you add a tool.
Years of tuning at risk
Your detection rules, playbooks, and configurations took years to build. Migrating to a new platform means starting from zero.
Compounding vendor lock-in
Every new AI platform you evaluate asks you to commit your data and workflows into their proprietary layer—one dependency for another.
Coverage gaps during transition
Any significant platform migration creates a window of reduced visibility. For a SOC or MSSP, that window is unacceptable.
The AI surcharge problem
Most platforms that offer AI capabilities charge a separate fee for the privilege — on top of model costs you're already paying to your LLM provider.
Grid is the headless SOC
Grid is purpose-built for AI agents to operate on. The tooling agents need to investigate, respond, and manage operations is built into the platform. Agents work with what your environment already produces, with no integration chain setting the ceiling on what they can see or do.
Competing products ship AI features built on a generalized model of security environments. Grid agents are defined, scoped, and governed by your team.
This is the headless SOC.
Get AI operators running on your existing telemetry.
Three steps, nothing displaced. That's the scale of involvement.
Create an account
Free, no credit card. Single form. Your Grid workspace is live in seconds. MSSPs can provision a hundred tenant orgs from the same place.
No procurement, no hardware,
no implementation partner.
Create an account
Free, no credit card. Single form. Your Grid workspace is live in seconds. MSSPs can provision a hundred tenant orgs from the same place.
No procurement, no hardware,
no implementation partner.
Connect a data source
An endpoint, a cloud log, a SaaS audit trail, whatever is closest to where you feel the most pain. Grid ingests it directly, in an AI-optimized format. Your tools keep receiving the same data on their own track.
No SIEM re-mapping
or index configuration
Connect a data source
An endpoint, a cloud log, a SaaS audit trail, whatever is closest to where you feel the most pain. Grid ingests it directly, in an AI-optimized format. Your tools keep receiving the same data on their own track.
No SIEM re-mapping
or index configuration
Get AI
Drop your LLM key like Anthropic, OpenAI, Google, or a local model. Set the guardrails for what agents can do autonomously. Watch the first operator run. Every action logged, every decision explainable.
No AI surcharge.
Pay your model provider at cost.
Get AI
Drop your LLM key like Anthropic, OpenAI, Google, or a local model. Set the guardrails for what agents can do autonomously. Watch the first operator run. Every action logged, every decision explainable.
No AI surcharge.
Pay your model provider at cost.
One AI FDE. One outcome. Continuous Coverage.
Assign a Forward Deployed Engineer (FDE) to own a specific security function: monitoring privileged accounts, tracking anomalous access patterns, or any persistent operational need in your environment. The FDE spins up the worker agents, owns their configuration, and supervises their results on an ongoing basis. When something breaks or goes quiet, it flags the issue and opens a case before it becomes your problem.
Configure agents
for the stack you have
Grid agents are defined by your team, not us. No vendor can ship an agent calibrated to your environment, your telemetry, and your workflows — and any that claims otherwise is selling a generalization. You set the scope, the permissions, and the approval thresholds.
and correlate with Okta logins to look
for suspicious access patterns.
Built in governance, not bolted on.
Governance in Grid is part of what every agent scaffolds from the start, not a separate configuration layer added after deployment. Every output is a discrete, auditable artifact that can be inspected, modified, or reversed through the same API surface that created it.
That's what API-first from day one looks like in practice, as opposed to bolt-on AI capabilities layered over existing product architecture.
Your stack is already most of the way there.
Connect one source in the next twenty minutes
and put your existing telemetry to work.
The same team, operating at a different speed.
Grid doesn’t replace your stack. It runs alongside it. Once your sources are integrated, AI can act on all of them at once.
24/7 coverage
without headcount
Operators triage and respond around the clock across every tenant. Analysts focus on the cases that require judgment, not the ones that require presence.
24/7 coverage
without headcount
Operators triage and respond around the clock across every tenant. Analysts focus on the cases that require judgment, not the ones that require presence.
Cross-tenant queries
in natural language
"Which customers have this IOC?" runs across your entire MSSP portfolio in one prompt. The AI operator queries every connected source and returns a correlated answer.
Cross-tenant queries
in natural language
"Which customers have this IOC?" runs across your entire MSSP portfolio in one prompt. The AI operator queries every connected source and returns a correlated answer.
Detection engineering
at conversation speed
Write a detection in natural language, test it against a year of retained telemetry, push to production — in one session. No manual YAML, no staging environment required.
Detection engineering
at conversation speed
Write a detection in natural language, test it against a year of retained telemetry, push to production — in one session. No manual YAML, no staging environment required.
New tenants in minutes,
not days
MSSPs provision a new customer org (detection ruleset deployed, sensors configured, outputs wired) with a single API call or a conversational prompt.
New tenants in minutes,
not days
MSSPs provision a new customer org (detection ruleset deployed, sensors configured, outputs wired) with a single API call or a conversational prompt.
Retroactive hunting
at zero extra cost
New IOC discovered at 2AM? Run it against a full year of telemetry across every tenant before your customers are awake. Retention is included free.
Retroactive hunting
at zero extra cost
New IOC discovered at 2AM? Run it against a full year of telemetry across every tenant before your customers are awake. Retention is included free.
Every action logged,
nothing hidden
Every operator decision (every API call, every response action, every conclusion) is in a full audit trail you own. Observable, reversible, explainable to any stakeholder.
Every action logged,
nothing hidden
Every operator decision (every API call, every response action, every conclusion) is in a full audit trail you own. Observable, reversible, explainable to any stakeholder.
Most products in the market are AI assistants, not AI agents. AI assistants do not typically engage in self-directed actions like AI agents do... there has been agent washing where an assistive implementation has been packaged as an AI agent.
The parallel pipeline architecture means we're not touching what's already in production. AI operators get their own purpose-built data and tooling fabric from the same raw sources.
Founder & CEO, LimaCharlie
The gap between advice and action is widening.
Most AI security products advise analysts on what to do next. Grid operators investigate detections, execute responses, and manage infrastructure without waiting for a human to approve each step. Analysts stay focused on judgment calls — the cases that require context only they carry. Every quarter spent waiting for the right migration window is a quarter operating at advisory-AI speed while the rest of the field moves to agentic.
Parses logs, suggests
next steps
Investigates and responds autonomously
Requires replacing or centralizing your stack
Runs in parallel; same raw sources, separate pipeline, nothing replaced
Human required
at every decision point
Human set guardrails; operators execute within
Coverage limited
to staffed hours
24/7 across all tenants simultaneously
$120K–$360K/yr
for managed AI SOC
$0 AI surcharge
Bring your own LLM
Black-box model,
opaque decisions
Full audit trail,
every action logged
Keep your stack.
Run AI operators.
Connect one source today. Run your first operator before the end of the week.
Nothing in your environment moves.