If you protect small and mid-size businesses, the math is brutal: attackers automate, defenders tab-switch. Tool sprawl, thin margins, and manual triage make it challenging for Tier-2/Tier-3 MSSPs to scale without burning out their staff. The answer isn’t “another dashboard” – it’s automation that can look, decide, and act.
This post outlines a practical way to bring agentic AI to endpoint defense and forensics so MSSPs can ship enterprise outcomes to SMBs – without enterprise overhead. It draws on what we’re building at ThreatBreaker: an AI-native, agent-as-a-service platform designed for MSSPs who manage hundreds to thousands of endpoints across regulated verticals.
The status quo: too many tools, not enough outcomes
Operational drag. Many MSSPs juggle double-digit security tools per client. Every new agent adds policy drift, training time, and swivel-chair response.
Noisy visibility. Alert streams outpace human review. Analysts spend cycles suppressing “expected badness” (scheduled scripts, admin tools) instead of investigating high-signal behaviors.
SMB reality. A single breach can end a business. In manufacturing or healthcare, downtime isn’t a spreadsheet problem – it’s payroll, safety, and trust.
We don’t need more events, we need decisions – and, when confidence is high, actions – delivered at the endpoint.
Agentic AI (not just “AI-assisted”)
Classic “AI in cybersecurity” scores alerts. Helpful, but it still asks an analyst to push the button. Agentic AI adds goal-seeking behavior: it collects, analyzes, chooses, and executes within guardrails, then learns from outcomes.
For endpoint security, that loop looks like this:
Collect process lineage, command lines, kernel events, registry/filesystem touches, network egress, and user context.
Analyze behaviors (not just signatures) against TTPs, baselines, and LLM-augmented reasoning about intent.
Decide with confidence scoring and select a play (kill, quarantine, block, roll back, or observe).
Act locally with least-disruptive controls; escalate only when needed.
Learn via post-action forensics and operator feedback to tune policies.
Done right, agentic AI is EDR with an autopilot – and an autopilot that knows when to stay hands-off.
Forensics analysis by default
You can’t automate what you can’t explain. ThreatBreaker bakes forensics-quality artifacts into each response:
Deterministic timelines. We reconstruct execution trees with causality (who spawned what, from which parent, with which token).
Evidence packs. On containment, the agent snapshots volatile evidence (handles, memory strings, persistence keys, scheduled tasks, driver loads) under a case ID.
Delta diffs. Instead of full disk images, we ship change sets – the minimal bytes/keys that matter. Faster to move, easier to reason about.
One-click replay. Analysts can “replay” the incident to see what the agent saw when it made a decision. That transparency builds trust.
Result: junior analysts close tickets with senior-level confidence, and auditors get traceable proof of what happened and why.
Where EDR ends and agentic AI begins
Traditional EDR is great at showing, but it’s cautious about doing. We keep EDR’s strengths and add controlled autonomy:
Policy-aware actions. Tenant and global guardrails govern behavior (e.g., allow signed RMM during maintenance windows; quarantine only above a confidence threshold).
Safe rollbacks. When the agent kills a process or quarantines a file, it records the delta so you can revert with one click if it blocked a legitimate – but unusual – workflow.
Multi-tenant controls. MSSPs can tune aggressiveness per client (observe-only for sensitive medical devices; “contain on sight” for high-risk finance endpoints).
Think EDR + MDR muscle in one lightweight agent, tuned for outsourced defense.
AI cybersecurity in practice: three high-value plays
Early ransomware choke-points. The agent watches the pre-encryption dance – shadow copy deletion, suspicious LSASS access, rapid tree-walks – and intervenes before damage, not after. It attaches a mini-forensics bundle so analysts can confirm it wasn’t a noisy backup job.
Living-off-the-land misuse. A single command line can be ambiguous; behavior over time isn’t. The agent correlates PowerShell, WMI, and credential-dump attempts and blocks the chain, not just one process, while preserving evidence.
Suspicious outbound C2. Rather than blanket-blocking domains, the agent weighs process ancestry, new binary network behavior, and DNS entropy. If confidence is high, it kills the origin process, isolates the host, and opens a guided investigation with packet captures around the decision point.
Built for MSSPs: outcomes and unit economics
Plug-and-play onboarding. One endpoint agent and a multi-tenant MSSP dashboard – no SIEM build-out required to get value.
Lower tool count. Replace a stack of collectors and ad-hoc scripts with one agent that sees, decides, and acts. Fewer renewals, fewer integrations to babysit.
Predictable pricing. Starting from $14.99 per endpoint/month, with custom branding and white-label/MSP licensing available.
Service upsell. Evidence packs and policy controls make it easy to productize “Threat Hunt Lite,” “Compliance Readiness,” or “Ransomware Readiness” tiers – without adding headcount.
Net effect: higher gross margin per endpoint, faster MTTR, and happier analysts.
What “good” looks like (KPIs to track)
To prove the value of agentic AI + EDR, we track a few simple numbers that tie directly to outcomes, not vanity metrics.
MTTD/MTTR: seconds to detect; minutes to contain.
False-positive retreat rate: how often analysts roll back an automated action – trending down as the model learns each tenant.
Analyst span: endpoints per Tier-1 analyst without alert fatigue.
Ticket closure quality: % of incidents closed with a timeline + evidence pack.
Downtime avoided: especially in manufacturing and healthcare, where minutes matter.
These KPIs tell us not just that the system works, but that it works better over time.
Go-to-market focus
Translating those outcomes into a repeatable motion requires a tight GTM focus:
Target customers: Tier-2/Tier-3 MSSPs managing 500–10,000 endpoints.
Primary verticals: Manufacturing, Healthcare, Professional Services, Logistics (compliance + uptime pressure).
Geography: US, UK, EU, with regional partners and community events to build trust.
Current status: Customer development & ICP validation, with signed LOIs and early-stage MSSP partners.
In short: measure what matters, point it at customers who feel the pain, and scale through partners who can deliver it repeatedly.
Call for pilot partners
Agentic AI doesn’t replace analysts, it amplifies them. For MSSPs, that means speed with proof, better margins, and a branded platform you can scale.
If you’re part of the MACH37 community and want to co-design pilots this fall, we’d love to connect: https://www.threatbreaker.com/.
By Andrew Sydoruk, Andrew Linskyi, and Yuriy Nayda, Founders of ThreatBreaker