❗️ For MSSPs, every new client adds headcount before margin. So how do you scale?
Teams breaking that cycle aren't hiring faster, they're investigating faster.
⚡️ See how #ANYRUN cuts analysis time, letting you handle more clients without extra hires: https://any.run/mssp/?utm_source=mastodon&utm_medium=post&utm_campaign=grow_your_mssp&utm_term=280426&utm_content=linktomssplanding
Most AI SecOps vendors ship a fixed platform: the architecture, the workflows, the pricing model are all decided for you.
LimaCharlie's position has always been the opposite. Build the capabilities and the value first, then give operators the freedom to modify, assemble, and build on top of them however their operation requires.
That extends all the way up the stack, from automated agents to deployable AI SOCs you define and run across thousands of tenants as infrastructure as code.
Your toolkit, built on real SecOps infrastructure.
See how it works: https://limacharlie.io/
An MSP idea is easy.
Building a scalable MSP is not.
Structure, delivery, and go to market decide everything.
MSP LaunchPad helps you go from idea to a live MSP with clarity and confidence.
Build it right from day one.
Explore more www.halexo.com
Token-based billing sounds reasonable until you run the numbers at MSSP scale.
With thousands of tenants, variable alert volumes, and no predictable ceiling on monthly AI costs, that model doesn't just create budget problems, it makes AI operationally impossible to commit to.
ASW pricing is structured differently: a flat monthly fee per analyst, covering everything they need. No per-token math, no worst-case scenarios to hedge against, no surprises when a tenant has a bad week.
Predictable costs are what make it possible to actually build AI into how you run a SOC, not just pilot it.
Explore pricing at http://limacharlie.io/pricing
Most tools that give you deep forensic flexibility weren't built for enterprise scale. And most enterprise tools weren't built by people who actually work incidents.
John Strand, Owner of Black Hills Information Security, says LimaCharlie is the exception.
During an active incident, the BHIS SOC can pull the telemetry and data they need quickly, without query caps, unnecessary clicks, or waiting.
LimaCharlie delivers security as composable, API-first primitives, giving teams full control over how they collect, query, and act on telemetry. All of it normalized to a single JSON format, stored free for a rolling year, and queryable when it matters most.
Learn more: https://limacharlie.io
Today at 10am PT / 1pm ET, we're showing what running a SOC on Claude Code looks like in production.
LimaCharlie CEO Maxime Lamothe-Brassard is walking through live demonstrations inside the Agentic SecOps Workspace, covering:
> Detection triage end-to-end, from alert to case
> Composable agent stacking: triage, false positive baselining, and threat intel
> The lc-agents repo: fork, extend, or contribute your own
Join the session: https://limacharlie.wistia.com/live/events/n78fkyeer5?utm_campaign=webinar+SOC+operations&utm_source=Mastodon&utm_medium=social
Two days until we show what a SOC built on infrastructure-as-code actually looks like in production.
After RSAC, the questions kept coming: how do the agentic operations actually work, and what does it look like beyond the demo?
This session is built for security engineers and MSSP operators who want those answers.
This Wednesday at 10am PT, LimaCharlie CEO Maxime Lamothe-Brassard covers the composable agent architecture, the SOC as IaC model, and the open-source lc-agents repo.
Add it to your calendar: https://limacharlie.wistia.com/live/events/n78fkyeer5?utm_campaign=webinar+SOC+operations&utm_source=mastodon&utm_medium=social
The security vendors racing to build proprietary AI models are solving the wrong problem.
Models aren't the bottleneck. The platform is.
Six months from now, the models available to your team will be dramatically better than what exists today. The question is whether your security infrastructure can actually use them.
LimaCharlie doesn't compete in the model race. We built the platform so any model can access 100% of platform capabilities through the same APIs your analysts use.
That parity is what makes the next layer possible: automated agents, and eventually deployable AI SOCs that run as a collection of agents across thousands of tenants at once.
Register for our next AI SecOps Workshop, where we'll use Claude Code with LimaCharlie to deploy agents, build detections, and catch issues before they become incidents: https://limacharlie.wistia.com/live/events/oz9xzr9fk3?utm_campaign=ai+workshop+cloudops+4+2026&utm_source=mastodon&utm_medium=social
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