WAVE 1 · DETECTION
Detection
1990s – 2010s
14,000 incidents/day. Half never investigated.
YOUR TEAM IS BURIED
Self-Improving SecOps.
Defense that compounds.
Simbian's Self-Improving SecOps is the autonomous security platform where offensive and defensive AI agents share one memory. Every attack makes your defense sharper.
Trusted by 175+ enterprises, six of the Fortune 500, and the world's largest MSSPs.
Trusted by leading enterprises and MSSPs
eBook
Security for Winners
Webinar
Why LLMs Fail in the SOC
Research
Simbian Research: The Cyber Defense Benchmark
What makes SecOps actually self-improving?
Self-Improving SecOps is the security platform where offensive and defensive AI agents share one memory, learn from every cycle, and get sharper every time they run. Five properties make that real.
Designed to think, not just follow.
Your platform handles the alert it has never seen before. No playbook required. Simbian reasons through it instead of failing the moment reality goes off-script.
SOAR breaks on anything the playbook did not anticipate.
Decisions are the bottleneck.
SecOps has been through two waves. First, detection scaled signals. Then automation scaled actions. Both helped, neither finished the job. The third wave is starting now, and it is the one where decisions, not signals, become the bottleneck.
WAVE 2 · AUTOMATION
Automation
2010s – 2020s
SOAR caps at ~25% automation. Novel attack? Playbook breaks. Your team is on call again.
STATIC DEFENSE FOR A MOVING TARGET
WAVE 3 · DECISIONING
Decisioning
Now
AI-ATTACK CONVERSION RATE: 0%
THE THIRD WAVE DOES NOT CATCH AI ATTACKS. IT STOPS THEM. THEN IT GETS SHARPER FOR THE NEXT ONE.
Is your SecOps self-improving?
Where your SecOps actually sits on the self-improving curve. Seven questions, two minutes. A real diagnosis of the gaps a real attacker would walk through.
Question 1 of 7
Does your platform reason from context instead of executing static playbooks?
One platform. One memory.
Every agent shares it.
Pentest finds the gap. SOC catches the alert. Threat Hunt chases novel patterns. Every action lands in Context Lake, and the next agent inherits it.
AI Pentest Agent
Continuous, on-demand pentesting with built-in remediation guidance. Pentesting stops being a quarterly compliance task. It becomes an “anytime you need it” security practice.
AI SOC Agent
Every alert investigated with full vulnerability context from Pentest. A noisy alert becomes a real threat when SOC sees it exploits a known gap. Triage in minutes, not hours.
AI Threat Hunt Agent
While SOC catches the known, Threat Hunt chases the novel. Parallel hypothesis testing across attack paths surfaces low-and-slow campaigns your detection rules never named.
Simbian Context Lake™
Every action, every verdict, every override flows into one shared memory. The longer Simbian runs in your environment, the smarter every agent gets.
Watch your MITRE ATT&CK coverage compound.
Most security teams measure coverage once a year, in slideware. This is one real customer, three cycles, ninety days, technique by technique. Watch the map fill in.
CYCLE 1
CYCLE 2
CYCLE 3
Initial Access
T1.11
T1.12
T1.13
T1.14
T1.15
T1.16
Execution
T1.21
T1.22
T1.23
T1.24
T1.25
T1.26
Persistence
T1.31
T1.32
T1.33
T1.34
T1.35
T1.36
Privilege Escalation
T1.41
T1.42
T1.43
T1.44
T1.45
T1.46
Defense Evasion
T1.51
T1.52
T1.53
T1.54
T1.55
T1.56
Credential Access
T1.61
T1.62
T1.63
T1.64
T1.65
T1.66
Discovery
T1.71
T1.72
T1.73
T1.74
T1.75
T1.76
Lateral Movement
T1.81
T1.82
T1.83
T1.84
T1.85
T1.86
Collection
T1.91
T1.92
T1.93
T1.94
T1.95
T1.96
Command & Control
T1.101
T1.102
T1.103
T1.104
T1.105
T1.106
Exfiltration
T1.111
T1.112
T1.113
T1.114
T1.115
T1.116
Covered
Uncovered
HOW SIMBIAN ACHIEVES THIS
CYCLE 1
33% COVEREDCycle 1: First campaign run.
We test six techniques. Threat Hunt finds three in logs, already in the environment. SOC detects two of six. Detection Engineering ships three new rules and tunes one.
CYCLE 2
56% COVEREDCycle 2: Rules from cycle one are live.
We retest the original six plus three new techniques. SOC now detects five of nine. Zero false positives. Four more rules ship.
CYCLE 3
83% COVEREDCycle 3: Red team runs evasion variants.
Obfuscated payloads. The kind of thing that breaks rules written too narrowly. Rules hold. SOC detects ten of twelve. Two remaining gaps close in the same cycle.
Self-improving, not self-driving.
You get the speed of AI without losing control. Insert human review and approval at any point. Every agent decision is logged and overridable. Every result and every feedback improves the system.
Your team oversees every containment action.
Agents do the mechanical work from day one, like investigation, evidence, and verdict. The hard calls, like quarantine, disable, and escalate, can stay with you until the agents prove themselves.
You can audit any agent decision in one click.
TrustedLLM logs every reasoning step. Override any verdict; your override teaches the next agent.
Enable automation on your timeline.
Three phases: shadow mode, assisted mode, then autonomous for the actions and environments you have signed off. Per skill. Per shift. You set the pace.
Agents act. Humans steer. That is the contract.
YourSOARdoesn’t work anymore.
The SecOps tools you have in place today won’t protect you tomorrow.
Approach
Their model
Self-Improving SecOps
SOAR
Rules and playbooks. Brittle, maintenance-heavy, ~25% ceiling.
Reasoning over rules. No playbooks. Agents that improve with use.
AI copilots
Investigate when humans prompt. Off-hours exposure.
Investigate and respond 24x7x365. Agents act; humans steer.
XDR
Correlates within one vendor data.
Federated reasoning across 100+ tools. No rip-and-replace.
Isolated AI Agents
Agents from different companies chain but do not learn from each other.
One Context Lake. Every finding teaches every agent.
Single-domain tools
Own one side of the loop. The handoff to the other side lives in tickets and backlogs.
Offensive and defensive agents on one substrate. The handoff is the platform.
SOAR
Rules and playbooks. Brittle, maintenance-heavy, ~25% ceiling.
Reasoning over rules. No playbooks. Agents that improve with use.
AI copilots
Investigate when humans prompt. Off-hours exposure.
Investigate and respond 24x7x365. Agents act; humans steer.
XDR
Correlates within one vendor data.
Federated reasoning across 100+ tools. No rip-and-replace.
Isolated AI Agents
Agents from different companies chain but do not learn from each other.
One Context Lake. Every finding teaches every agent.
Single-domain tools
Own one side of the loop. The handoff to the other side lives in tickets and backlogs.
Offensive and defensive agents on one substrate. The handoff is the platform.
Built for enterprise security and the MSSPs that scale them.
Enterprise security teams
100% alert coverage without scaling headcount.
One platform across SOC, threat hunt, pentest, and NetSecOps, so the loop closes inside your team, not across vendors.
Explore enterprise →MSSPs run more clients with the same team
$25M+ legacy spend removed across 750+ deployments.
A substrate built for multi-tenant scale: same agents, same Context Lake, customer-by-customer learning.
Explore MSSP / MDR →Frequently asked questions
Self-Improving SecOps is a security operating model where offensive and defensive AI agents share one Context Lake. Every pentest finding becomes a detection. Every triaged alert teaches the next agent. Coverage compounds with use instead of decaying between audits.
SOAR runs static playbooks you have to maintain. Copilots suggest; humans still click. Self-Improving SecOps closes the loop: agents act inside a governed boundary, every action writes back to the Context Lake, and the next cycle starts smarter. No playbook rewrite. No prompt tuning.
No. Agents do the mechanical work, like investigation, evidence, and verdict. The hard calls, like quarantine, disable, and escalate, stay with your team. You ramp from shadow mode to assisted to autonomous, per skill, per shift. TrustedLLM logs every decision; you can audit and override anything.
Days, not quarters. Most customers see initial coverage data inside two weeks and full Context Lake integration with their SIEM, EDR, IdP, and ticketing inside 30 days. No professional services tax, no rip-and-replace.
We measure MITRE ATT&CK technique coverage before and after deployment. In a typical 90-day window, coverage moves from 33% to 83%, roughly 50 new attacker techniques covered without adding a single analyst. You see the curve in your environment, not a slideware claim.
Yes. Built for MSSPs at scale: multi-tenant isolation, per-customer Context Lakes, white-label dashboards, and the ability to deploy the same agent fleet across hundreds of tenants without linear analyst growth. Margin per customer goes up; mean time to value goes down.
What Our Customers Say
Simbian's AI Agents consistently deliver precise and accurate responses, significantly easing our workload. What used to take days now takes minutes, and we're thrilled with how seamlessly it integrates into our existing processes. It's not just about saving time; it's about maintaining the highest standards of security and accuracy, which is exactly what Simbian enables us to do.
Matillion
Suchit Mishra
Director of Information Security
Security is a domain of ever-increasing complexity. Every day a security incident brings new variables. Simbian is building a fully autonomous security platform. We are excited to partner with them as it allows us to be strategic in our security goals, leaving mechanics of security to Simbian.
Axelar
Sergey Gorbunov
Co-founder
Security partners, especially MSSPs and MDRs, are at a critical juncture. Attacks are getting accelerated with AI. We must use AI on defense side too. We have gotten great support from Simbian with its fully autonomous security. It allows us to do more with less, directly impacting both our top and bottom lines.
Cybalt
Khirodra Mishra
CEO
Simbian's platform takes a straightforward approach to solving core problems we see every day in the SOC. The power in the platform, their AI agents, is in its simplicity. They are not adding steps and processes to achieve results. The Security Accelerator platform drives efficiency without sacrificing efficacy. It allows us to shift the role of the analyst; to give them the time to use human insight, because well trained AI that we can review, and audit, is immensely powerful. It sets a whole new bar for security operations.
SMT
Mohammad Qasas
SOC Lead
Simbian's AI agents augment and automate many security services resulting into better efficiencies and increased precision.
Wipro
Siva VRS
Vice President
What Simbian's doing in that space has really been a differentiator and a game changer for how my team's thinking about these problems. We're no longer thinking about a pipeline of work that we've got to have 20 people to solve.
Bottomline
Blaine Brennecke
Director of Security Operations