MSOC is a fully autonomous Security Operations Center powered by Milind AI — a workforce of 36 AI employees that detect, triage, investigate, hunt, respond and report around the clock. Not a SIEM with a chatbot bolted on. A complete operating system for security operations that detects and contains threats in under two minutes.
You were sold three products and a team to run them. MSOC is the one autonomous platform that does all three.
Unified ingest, normalization and pattern matching across all your sources — no fragmented log management, no schema wrangling.
The workforce triages continuously with no queue and no shift handoff. False positives are auto-closed at 95%+ precision; escalations carry a full evidence trail and confidence score.
Immediate containment with per-client approval policies. Full Jira ticketing, SLA tracking, and weekly reporting — automated, no analyst required.
Sample case: EDR alert (encoded PowerShell on FIN-WS-218) → verdict TRUE POSITIVE / T1059.001 → contained in 01:38, endpoint isolated, client notified.
The only question is whether you keep your existing tooling or you want us to close the gaps. Everything else — the workforce, the detection engineering, the hunting, the reporting, the sub-2-minute response — is identical in both.
36 AI employees, 24/7 · detection engineering and self-tuning (1,700+ rules across 17 MITRE categories) · threat hunting (500+ playbooks, MÍMIR threat intel) · identity baselining and UEBA · automated response under per-client policy · sub-2-minute MTTD and MTTR · case, incident and executive reporting · SLA tracking, Jira/ITSM, SAML SSO, RBAC · continuous exposure and credential-leak monitoring · data residency of your choice.
Run fully autonomous or human-in-the-loop — your call, either model.
You keep everything you already run. We integrate on top.
We replace what is underperforming and add what is missing.
These numbers come from production environments, not benchmarks. The 93% figure is our fleet average; at our largest client the reduction is 99.9% — see the results below.
Through learned FP suppression and intelligent deduplication.
Streaming, event-driven ingest — detection fires as the telemetry lands, not on a scan interval.
End-to-end and inclusive of detection — signal to triage to verdict to containment.
Without shift scheduling, overtime, or analyst burnout.
Lower operational cost vs. equivalent traditional SOC staffing.
Real client environments running in the MSOC customer portal — not benchmarks, not projections.
~31,000 employees. ~11 TB of security telemetry per day. Roughly 5,000 raw alerts every hour — about 120,000 a day. MSOC reduced that to ~100 items per day that genuinely warranted attention, and built a per-identity UEBA baseline across all ~31,000 identities from a full year of historical data in under two hours — establishing both what normal looked like and what was already compromised before we arrived.
A flood of benign platform activity from cloud configuration and management tooling was generating tens of thousands of false alerts. MSOC’s severity governance and self-learning legit-tool suppression cut roughly 70,000 false positives to near zero, and automatically validated 150+ privileged-group and brute-force alerts as benign policy activity through telemetry lookback.
MSOC detected an unauthorized remote-management agent and a malware incident across the dealer fleet, quarantined the malicious files, and safely reconnected dozens of endpoints after validation — while correctly never disrupting legitimate dealership business software.
A suspected business-email-compromise was investigated end-to-end and correctly cleared as a false positive — a local send from an unlocked workstation, not an account takeover — avoiding an unnecessary organization-wide password reset and the downtime that comes with it.
MSOC’s response guardrails prevented automated isolation of a domain controller and a perimeter firewall on noisy inbound triggers, holding action until the signal was validated.
Continuous credential-leak and infostealer monitoring surfaced breached credentials tied to live user accounts before they were used for access.
Client identities withheld pending permission. Named references and logos available on request.
Most “AI” tools still need a full SOC team to run them. MSOC replaces the team.
| Capability | Traditional SOC / MDR | AI Copilot Tools | MSOC · Mjölnir |
|---|---|---|---|
| Alert Triage | Manual, L1 analyst-dependent | AI suggests, human decides | Fully autonomous — AI triages, learns and auto-closes FPs |
| Mean Time to Detect | Minutes to hours, batch-dependent | Depends on the underlying SIEM | Under 2 minutes — streaming, event-driven |
| Mean Time to Respond | 30–60 minutes | 15–30 minutes | Under 2 minutes, end-to-end |
| Detection Rules | Vendor-provided, generic | Limited, requires tuning | 1,700+ proprietary rules, auto-tuned per client |
| Threat Hunting | Manual, ad-hoc, senior-only | Query assistance | Automated hypothesis generation + 500+ hunting playbooks |
| Response Actions | Ticketing only, manual execution | Recommends actions | Automated kill, quarantine, isolate — with approval controls |
| False Positive Handling | Repetitive manual review | Some pattern detection | Auto-learns FP patterns, suppresses across all clients |
| Staffing Requirement | 6–12 analysts for 24/7 coverage | Still needs full SOC team | Zero for autonomous mode, or amplify your existing team |
| Transparency | Weekly PDF reports, limited visibility | Chat-based interaction | Full evidence trail, live dashboards, every decision auditable |
Signals classified, deduplicated and triaged autonomously across the full workforce — no queue, no shift handoff. False-positive patterns are learned and suppressed automatically.
Dedicated detection-engineering employees learn false-positive patterns and tune rules per client with no analyst effort. Accuracy compounds: at one client, self-learning suppression of benign platform activity removed roughly 70,000 false positives with zero real threats missed.
Per-identity behavioural baselines built from historical data, establishing both what normal looks like and what was already compromised. At our largest client we baselined ~31,000 identities across a full year of data in under two hours.
Every alert mapped to tactics and techniques. Playbooks trigger on technique combinations, not keywords. 1,700+ rules span 17 MITRE categories.
564 hunting queries across 9 SIEM platforms, with AI-driven hypothesis generation. Intel-driven hunts and exposure scoring (KEV/CVE against your actual stack) surface threats before they trigger a classic alert.
False-positive and detection patterns learned at one client propagate across the fleet. A pattern seen once strengthens detection everywhere — without sharing client data between tenants.
Kill processes, quarantine files, isolate endpoints, block hashes — with per-client approval policies. Guardrails hold action on critical infrastructure until the signal is validated, so response never causes the outage.
Standing watch for breached credentials, infostealer logs, and KEV/CVE exposure across your stack — surfacing compromised accounts before they are used for access. Not an add-on.
Per-client, per-severity SLA tracking with automated escalation as thresholds approach. Case, incident and executive reports generated and delivered on a schedule, client-branded.
Message an AI employee — the SOC Manager, a hunter, an investigator — and ask a question in plain language. It consults the right specialists and answers with live SOC data, in your own tone and channel.
Query your entire telemetry estate through the client portal in plain language — across every connected data source, without writing platform-specific queries or knowing which system holds the answer.
500+ data sources across SIEM, endpoint, cloud, network, identity, email, SaaS, container, data, OT/ICS and infrastructure environments. Data residency of your choice (default: Canada). Preferred platforms are Sumo Logic and SentinelOne — everything else integrates natively.
★ Preferred platform · A representative selection of the 500+ sources MSOC ingests — don’t see your stack? We add new sources on request.
All plans: 100% Canadian-owned, data residency of your choice, no CLOUD Act risk. The workforce, detection engineering, hunting and reporting are identical in both models — only the tooling question differs.
Integrates with what you already run. No rip-and-replace, no new licences.
We close the gaps — replacing what underperforms and adding what is missing.
White-label the whole platform. Isolated tenants, dedicated SLAs, full DFIR depth.
From $50K/yr all-in · vs. $40K–$56K/yr for comparable enterprise MDR