AI-Powered Cybersecurity · Now Live

Stop breaches
before they cost you.

Enterprise-grade threat intelligence — built for every audience. Board-ready risk briefs. CISO-level compliance coverage. SOC analyst speed. AI/ML transparency via SHAP. Drop any log file, get actionable intelligence in 60 seconds. No agents. No onboarding.

Start Free Trial See 29 Models
SOC 2 Compliant
<2s Analysis
94% Accuracy
No Agents
Jira · ServiceNow
Threat Detected
OT Command Inject
Confidence: 93.7% · CRITICAL
Models Active
29 / 29
All systems operational
Risk Score
92 / 100
Escalate · Jira ticket opened
Analysis Time
1.4s
1,240 log rows · IAM Cloud
ITSM Action
ServiceNow
INC0048293 · Auto-created
0
ML Models
0%
Detection Accuracy
0
Compliance Frameworks
0
ITSM Integrations
<2s
Analysis Time
0×
Lower Cost than SIEM
60s
First Insight
Why SHIELD

Built different. Priced for real teams.

Every competitor makes you choose between coverage, cost, and complexity. SHIELD eliminates that trade-off.

🚀
Live in 60 Seconds. Not 6 Months.
Upload any log file in any format, get intelligence immediately. No agents. No professional services engagement.
vs 3–6 month average SIEM deployment
💰
$228/mo vs $20,000+/mo. Same Intelligence.
29 purpose-trained ML models and full compliance monitoring at a fraction of SIEM cost. No hidden add-ons.
10× lower cost than SIEM — same coverage
🔗
ITSM & SOAR — Analysts focus on decisions, not admin.
Auto-create Jira, ServiceNow, and Freshdesk tickets the moment anomalies are detected. SOAR playbooks handle escalations, IP blocks, and notifications — freeing analysts from repetitive workflow overhead.
3 ITSM platforms · 6 SOAR actions · Zero manual ticket creation
🧠
Explain Every Alert to Your Board.
SHAP factor charts show exactly which log columns drove the risk score in plain language — for board presentations, auditors, or SOC escalations.
Defensible evidence — no black-box guesswork
🏭
OT/SCADA, Containers & Cloud IAM. Gaps your SIEM ignores.
7 new log types cover the attack surfaces traditional SIEMs leave blind — industrial control systems (Modbus, DNP3), Kubernetes runtime, AWS CloudTrail IAM, DLP, NAC, MFA bypass, and API gateways.
29 log types — from DNS to OT/SCADA · One platform
📋
12 Compliance Frameworks — No Extras.
GDPR, HIPAA, PCI-DSS, SOC 2, ISO 27001, NIST CSF, DORA, HITECH, 21 CFR Part 11, NERC CIP, IEC 62443, OWASP — activated by sector at registration.
Sector-aware: pharma, energy, finance, healthcare
SHIELD vs The Alternatives
CapabilitySHIELD v6.0Generic SIEMRules-based IDS
Setup time< 60 secondsDays–weeksWeeks–months
Log types covered29 (auto-detected)Varies (manual config)Limited
OT/SCADA support✓ Native (Modbus, DNP3, OPC-UA)Add-on✗ None
ITSM integrations✓ Jira · ServiceNow · FreshdeskVaries✗ None
SOAR playbooks✓ Built-inAdd-on / extra cost✗ None
Compliance frameworks12 built-in · sector-awareAdd-on modules✗ None
NLQ — ask in plain English✓ Built-in✗✗
MITRE ATT&CK mapping✓ Per-alertPartial✗
Starting price$228 / mo$2,000+ / mo$500+ / mo
Full-Spectrum Coverage

Every attack surface. Every log type.

SHIELD auto-detects your log format by filename and content, then routes to the right specialist model — no configuration needed.

Threat Detection · 13 Log Types
🔍
DNS
DDoS, DNS Poisoning, DGA/Exfiltration, NXDOMAIN. SLD entropy, TTL, query-name analysis.
17 features
🛡️
Firewall
Port scanning, DDoS, brute force, intrusion attempts. Protocol & packet-level analysis.
9 features
📧
Email Security
Phishing, BEC, spam, malware delivery. SPF/DKIM/DMARC validation, subject entropy scoring.
10 features
🌐
Network / NetFlow
DDoS, port scans, lateral movement, C2 beaconing, data exfiltration via traffic baselines.
10 features
💻
Endpoint / EDR
Malware, ransomware, fileless attacks, rootkits, USB exfiltration. Process & memory analysis.
10 features
☁️
Cloud / CloudTrail
Misconfiguration, IAM privilege escalation, cryptomining, supply chain. AWS/Azure/GCP.
10 features
🔑
Identity / IAM
Unauthorized access, MFA bypass, token theft, directory enumeration, shadow IT. SSO/LDAP.
10 features
👤
User Activity / UEBA
Account takeover, insider threats, credential stuffing, session hijacking. Geo-velocity.
10 features
🗄️
Database
SQL injection, data exfiltration, schema modification, privilege escalation. MySQL/MSSQL/PG.
10 features
🖥️
Web Server
DDoS, scraping, credential stuffing, directory traversal, bot activity. Apache/Nginx/IIS.
10 features
⚙️
Application
SQL injection, XSS, API abuse, path traversal, remote code execution via app logs.
10 features
🖱️
System / Syslog
Kernel exploits, cron tampering, log clearing, service disruption, resource exhaustion.
10 features
📋
Audit Logs
Policy violations, unauthorized changes, data tampering, audit log tampering.
10 features
New in v6.0 · 7 Log Types · Industrial, Cloud-Native & Modern Attack Surfaces
🏭
OT / ICS / SCADA NEW
Modbus, DNP3, OPC-UA, IEC 104. Cross-zone IT→OT movement, unauthorized writes, firmware tampering, replay attacks.
12 features
📦
Container / K8s NEW
Docker runtime & Kubernetes audit. Privilege escalation, container escape, malicious images, RBAC abuse, cryptomining.
16 features
🔌
API Gateway NEW
Rate limit evasion, JWT theft, bot traffic, SQL injection via API, data harvesting. Kong, AWS APIGW, Nginx, Apigee.
20 features
☁️
Cloud IAM NEW
AWS CloudTrail, Azure AD, GCP IAM. Root account usage, console-without-MFA, cross-account abuse, access key leaks.
11 features
🔒
Data Loss Prevention NEW
Forcepoint, Symantec, Microsoft DLP. Intentional leak, bulk download, after-hours transfers, external destination detection.
11 features
🚧
Network Access Control NEW
Cisco ISE, Aruba, Forescout, ClearPass. Rogue devices, MAC spoofing, posture violations, brute force RADIUS.
10 features
📱
MFA Events NEW
Duo, Okta, Azure MFA, RSA SecurID. MFA fatigue attacks, SIM swap, OTP phishing, token replay, bypass detection.
14 features
Intelligence & Monitoring · 4 Engines
🔐
Security Events / SIEM
Cross-source correlation, authentication events, broad security log analysis.
Multi-source
🎯
Threat Intelligence
Known malicious IPs, phishing domains, malware hashes, ransomware IOCs, APT indicators. VirusTotal · AbuseIPDB enrichment.
10 features
🔎
Vulnerability Scans
Critical/High CVEs, misconfigurations, exposed services, weak credentials. Nessus/Qualys/Rapid7 compatible.
10 features
📡
Anomaly Detection
Unsupervised ML runs across all 29 log types — catching novel zero-day patterns no rule-based system can detect.
Unsupervised
Compliance Frameworks · 12 Standards · Sector-Aware, No Extra Modules
🔒
GDPR
Continuous monitoring against GDPR data processing and access control requirements.
All sectors
🏥
HIPAA
ePHI access monitoring, healthcare log analysis, audit trail generation for HIPAA controls.
Healthcare
💳
PCI-DSS
Payment log analysis, cardholder data environment monitoring, PCI requirement tracking.
Financial
🏛️
ISO 27001
Access control, asset management, incident response, and control effectiveness tracking.
All sectors
🛡️
SOC 2
Continuous monitoring against SOC 2 Trust Services Criteria — security, availability, confidentiality.
All sectors
🏛️
NIST CSF 2.0 NEW
Govern / Identify / Protect / Detect / Respond / Recover. Mandatory for US federal and defense-adjacent orgs.
Government
🇪🇺
DORA NEW
EU Digital Operational Resilience Act — mandatory for EU financial entities from Jan 2025.
Financial · EU
🏥
HITECH NEW
Extends HIPAA with breach notification and EHR audit requirements.
Healthcare
⚡
NERC CIP NEW
North American Electric Reliability Corp — mandatory for bulk electric systems.
Energy
🏭
IEC 62443 NEW
Industrial control systems & SCADA security standard for OT/ICS environments.
Energy · OT
🔬
21 CFR Part 11 NEW
FDA electronic records & signatures — mandatory for pharma, biotech, medical devices, CROs.
Life Sciences
⚖️
OWASP Top 10
Web application attack pattern coverage — injection, broken auth, XSS, SSRF, and more.
All sectors
💡 Compliance frameworks activate automatically based on your sector selection at registration. Switch or add frameworks any time in settings.
Process

Upload. Analyze. Act.

From raw log file to threat report — and auto-created ITSM ticket — in under 2 seconds. No agents. No configuration.

01
📁
Upload Any Log File
Drop any log — .csv, .log, .txt, .xls, .xlsx, or native SIEM exports. Dual-detection reads filename AND column content to auto-route to the right model across all 29 types.
Content-first detection
02
🧠
ML Classification
Each specialist model loads automatically, extracts domain-specific behavioural signals from your log data, and runs dual-layer threat scoring — supervised classification and unsupervised anomaly detection — in parallel. SHAP explainability is included on every prediction.
Specialist ML
03
⚖️
Risk Scoring
Multi-factor engine combines classification confidence, behavioural anomaly scoring, OWASP severity weighting, asset criticality, and regulatory multipliers (GDPR/HIPAA/PCI) into a normalised 0–100 threat score.
Multi-factor
04
📊
Actionable Intelligence
SHAP explainability charts, attack-specific remediation steps, MITRE ATT&CK tactic tagging, outlier CSV exports, executive briefings, and NLQ — ask your logs in plain English.
SHAP · MITRE · NLQ
05
🔗
ITSM & SOAR Response
SOAR playbooks auto-create Jira, ServiceNow, or Freshdesk tickets on anomaly detection. Configurable triggers by severity, log type, and attack class — with webhook, email, and IP-block actions.
Jira · ServiceNow · Freshdesk
SHIELD Analysis Output — iam_cloud_cloudtrail.log → ServiceNow INC auto-created
[ INFO ] Resolver v2 → log_type: iam_cloud (confidence: 0.97, method: source_hint/cloudtrail)
[ INFO ] Specialist Analyzer: Cloud IAM · Dual-layer threat scoring: ON
[ HIT ] threat: RootAccountUsage · confidence: 94.8% · score: 92/100
[ ] account_privilege: elevated · auth_posture: weak · access_pattern: anomalous
[ MITRE] TA0004 Privilege Escalation · T1078.004 Cloud Accounts
[ SHAP ] Risk factors identified · Account privilege (critical) · Auth posture (high) · Access pattern (elevated)
[ SOAR ] Playbook triggered: P0_ROOT_ESCALATION
[ ITSM ] ✓ ServiceNow INC0048293 created · Priority: 1-Critical · Assigned: SOC-L2
[ DONE ] Analysis: COMPLETE · 1.6s · SHAP ready · Jira webhook: 200 OK
Integrations & APIs

Connect your tools. Automate your response.

SHIELD integrates natively with your existing ITSM and ticketing stack. No middleware, no custom scripts — connect once and every anomaly auto-creates a structured ticket with full threat context.

Auto-create Jira issues with full threat context — attack type, risk score, MITRE tactic, SHAP factors, and affected assets — directly from SHIELD anomaly alerts. Supports custom project, issue type, and priority field mapping.
Create IssueUpdate StatusInbound WebhookBidirectional Sync
Automatically open ServiceNow incidents with P1–P4 priority mapped from SHIELD's risk score bands. Includes affected CI lookup via CMDB, assignment group routing, and status sync back to SHIELD on resolution.
Create IncidentCMDB LookupPriority MappingStatus Sync
Create Freshdesk tickets with structured threat descriptions, severity tags, and recommended response steps. Ideal for MSP and MSSP teams managing client security incidents across multiple tenants.
Create TicketSeverity TagsMulti-tenantInbound Sync
SOAR Playbook Actions

Configure triggers by severity level, log type, attack class, or risk score — then chain any combination of these automated response actions.

📨
ITSM Ticket
Auto-create in Jira, ServiceNow, or Freshdesk with full threat context
🔔
Webhook Alert
HMAC-signed webhook to Slack, Teams, PagerDuty, or any HTTP endpoint
📧
Email Escalation
Structured alert emails to SOC teams, managers, or compliance officers
🚫
IP Block
Auto-block malicious source IPs at the network perimeter — instant enforcement without manual firewall changes
🏷️
Tag & Classify
Auto-tag anomalies with MITRE ATT&CK tactics, severity bands, and log source metadata
📑
Compliance Report
Trigger auto-generation of framework-specific compliance reports on critical findings
REST API — Integrate SHIELD into Any Stack

Every SHIELD capability is available via authenticated REST API. Build custom dashboards, embed threat intelligence into your SIEM, or automate bulk log analysis.

POST
/predict
Single log inference — auto-resolves log type, enriches features, runs dual-layer AI threat analysis. Returns threat classification, confidence level, risk score, and SHAP explainability factors.
POST
/batch_predict
Batch inference for up to 500 logs per call. Groups by log type for efficient model loading. Returns ordered results with per-log attack classification.
POST
/resolve_type
Dry-run log type resolution — returns log_type, confidence score (0–1), and resolution method (explicit / source_hint / event_pattern / field_signature).
GET
/log_types
Lists all 29 supported log types with model availability, coverage scope, and current operational status for each analyzer.
POST
/nlq_query
Natural language query interface — ask questions about your logs in plain English. Returns structured results with affected entities and time ranges.
GET
/compliance_score
Real-time compliance score for any framework (GDPR, HIPAA, PCI-DSS, NIST CSF, DORA, etc.) based on current log coverage and anomaly history.
POST
/playbook/trigger
Manually trigger a SOAR playbook by ID. Useful for testing automations or triggering responses from external SIEM systems via webhook integration.
GET
/mitre_heatmap
Returns MITRE ATT&CK tactic coverage heatmap for the tenant — shows which tactics have been detected and their frequency over configurable time windows.
GET
/health
Service health check — lists all 29 active models, memory usage, cache status, SHAP availability, and current server-side latency metrics.
All endpoints are authenticated, encrypted in transit, and rate-limited. API documentation and integration guides are available to registered customers.
Threat Intelligence Enrichment

Every anomaly is automatically enriched with external reputation data — no manual lookups needed.

🦠
VirusTotal
IP & domain reputation, file hash lookup
🚨
AbuseIPDB
IP abuse confidence score & report history
🔭
Shodan
Open ports, CVEs, and asset exposure
🛡️
CVE / NVD
CVSS scores, affected versions & patches
Interactive Demo

See SHIELD detect threats live.

Pick any of the 29 log types, run the AI pipeline, and watch every stage — ingestion, ML classification, threat graph, risk scoring, SHAP explainability, and ITSM ticket creation — in real time.

SHIELD AI — 29 Log Types · Threat Detection Demo ↗ Open Full Screen
Platform Capabilities

Not just detection. Full intelligence.

SHIELD explains every threat, tells you exactly what to do, opens your ITSM ticket, and speaks it aloud if needed. Built for humans, not just machines.

🧠
29 Purpose-Trained Models
Every model trained exclusively on its own log type — from DNS to OT/SCADA to MFA events. Specialist training is why accuracy hits 94%, not dragged down by generic approaches.
📊
SHAP Explainability + MITRE ATT&CK
Every prediction includes a SHAP factor breakdown and MITRE ATT&CK tactic mapping — essential for SOC escalations, board reporting, and audit trails.
🔗
Native ITSM + SOAR Automation
Auto-create Jira, ServiceNow, and Freshdesk tickets on anomaly detection. SOAR playbooks configure webhook, email, IP-block, and compliance report triggers without code.
💬
NLQ — Ask Your Logs in Plain English
Natural language query interface lets non-technical users ask "which users logged in from unusual locations last week?" — no query language required.
🔊
Voice-Assisted Threat Narration
Configurable voice assistant reads threat summaries and recommendations aloud — critical events reach your team even off-screen.
📤
Outlier CSV Export + Executive Briefings
Download flagged rows for forensic investigation, or auto-generate board-ready executive briefings (CISO / Board / SOC audience) on demand or on schedule.
12 Compliance Frameworks — Sector-Aware

Built-in compliance.
Activated by your sector.

GDPRHIPAAPCI-DSSSOC 2ISO 27001NIST CSF 2.0DORAHITECHNERC CIPIEC 6244321 CFR Part 11OWASP Top 10
29 Log Types · Supported Formats
.csv.log.txt.xls / .xlsx dnsfirewallemail / smtpnetwork / netflow webserver / apache / nginxapplicationdatabase / mysql / postgres syslog / systemsiem / auth / securityidentity / ldap / sso / iam endpoint / edrcloud / aws / azure / gcpaudit / compliance user_activity / uebavuln / nessus / scanthreat_intel / ioc iso27001 / ismssoc2 ot_scada / modbus / dnp3 container / kubernetes / k8s api_gateway / kong / apigw iam_cloud / cloudtrail dlp / data_loss nac / radius / cisco_ise mfa / duo / okta / webauthn
← Upload from any tool — SHIELD auto-detects type and routes to the right model. Purple = new v6.0 types.
// Risk Factor Breakdown — Cloud Access Anomaly (Illustrative)
Account Privilege Auth Posture Access Pattern Service Sensitivity Cross-Boundary Access HIGH HIGH MED MED LOW
ML Model Matrix

29 purpose-trained. Independently versioned.

29 specialist models + anomaly engine. Each covers its own log type — retrain one without affecting any other. Model internals are kept confidential to protect detection integrity.

Model Log Type(s) Coverage Depth Attack Classes Status
DNS Threat Classifierdns, dns_query●
DDoSDNS PoisoningDGA/ExfilNXDOMAINNormal
● Active
Firewall Analyzerfirewall●
Port ScanDDoSBrute ForceIntrusion
● Active
Email Security Analyzeremail, smtp●
PhishingSpamBECMalware Delivery
● Active
Security Event Analyzersecurity, siem, auth●
Auth AttackPriv EscalationAnomalous Event
● Active
Anomaly Detection EngineAll 29 log types●
Zero-dayOutliersBaseline Deviation
● Active
Network Analyzernetwork, netflow●
DDoSPort ScanData ExfilC2 Beacon
● Active
Endpoint Analyzerendpoint, edr●
MalwareRansomwareFilelessRootkit
● Active
Identity & IAM Analyzeridentity, iam, sso, ldap●
Unauth AccessMFA BypassToken Theft
● Active
User Activity Analyzeruser_activity, ueba●
Account TakeoverInsider ThreatCred Stuffing
● Active
Cloud Security Analyzercloud, cloudtrail, aws, azure●
MisconfigurationIAM EscalationData Exposure
● Active
Web Server Analyzerwebserver, apache, nginx●
DDoSWeb ScrapingDir TraversalBot
● Active
Application Analyzerapplication, app●
SQL InjectionXSSAPI AbuseRCE
● Active
Database Analyzerdatabase, mysql, mssql●
SQL InjectionData ExfilSchema Mod
● Active
System / Syslog Analyzersystem, syslog, kernel●
Kernel ExploitCron TamperLog Clearing
● Active
Audit Log Analyzeraudit, compliance●
Policy ViolationData TamperingLog Tampering
● Active
Vulnerability Analyzervulnerability, nessus●
Critical CVEHigh CVEMisconfiguration
● Active
Threat Intelligence Analyzerthreat_intel, ioc●
Malicious IPPhishing DomainAPT IOC
● Active
OT/SCADA Analyzerv6.0ot_scada, modbus, dnp3, opcua●
Unauthorized WriteCross-ZoneCommand InjectReplayDoS
● Active
Container/K8s Analyzerv6.0container, kubernetes, docker●
Priv EscalationContainer EscapeRBAC AbuseCryptoMining
● Active
API Gateway Analyzerv6.0api_gateway, kong, apigw●
Rate Limit EvasionToken TheftBot TrafficSQLi
● Active
Cloud IAM Analyzerv6.0iam_cloud, cloudtrail, azure_ad●
Root AccountMFA BypassCross-AccountKey Leak
● Active
DLP Analyzerv6.0dlp, data_loss●
Intentional LeakBulk DownloadInsider Threat
● Active
NAC Analyzerv6.0nac, radius, cisco_ise●
Rogue DeviceMAC SpoofingPosture Violation
● Active
MFA Event Analyzerv6.0mfa, duo, okta, azure_mfa●
MFA FatigueSIM SwapOTP PhishingToken Replay
● Active
GDPR Compliance Analyzergdpr, access logs—
Data Access ViolationConsent BreachRetention Violation
● Active
HIPAA Compliance Analyzerhipaa, healthcare logs—
ePHI ExposureUnauth AccessAudit Gap
● Active
PCI-DSS Compliance Analyzerpci, payment logs—
CHD ExposureUnencrypted DataAccess Violation
● Active
ISO 27001 Analyzeriso27001, isms—
Access Control GapAsset ViolationControl Failure
● Active
SOC 2 Analyzersoc2, trust_services—
Security Criteria FailAvailability BreachPrivacy Violation
● Active
What Teams Say

Built for people defending the perimeter.

★★★★★
"We passed our SOC 2 audit first time, with zero findings. SHIELD's continuous compliance monitoring meant no surprises when auditors arrived. The Jira integration auto-created tickets for every finding — our team never had to touch a spreadsheet."
Head of SecOpsFinancial Services · 800 employees
★★★★★
"We replaced a $22k/month SIEM with SHIELD. The ServiceNow integration meant our SOC workflow didn't change — incidents still land in the same queue, just with far better context and 10× less noise."
CISOSaaS Platform · Series C
★★★★★
"We run OT and IT networks in the same facility. SHIELD is the only platform that covers both seamlessly — the OT/SCADA analyzer caught a cross-zone lateral movement attempt within seconds. Our board now receives an auto-generated risk brief every month. We didn't need a single consultant to onboard."
IT Security ManagerHealthcare & Energy Conglomerate · 2,400 employees
Who SHIELD is for

Built for every layer of your organisation.

From the board room to the terminal — SHIELD speaks every language. One platform, every audience.

Board & C-Suite
🏛️
Cyber risk in plain language. Defensible in the boardroom.
SHIELD translates log-level threats into financial risk, compliance posture, and executive KPIs. Auto-generated board briefings, audit-ready evidence packs, and a single risk score that doesn't require a security PhD to understand.
Avg. data breach cost: .45M · SHIELD pays for itself on day one
CISOs & Security Leaders
🛡️
29 specialist detectors. 12 compliance frameworks. One dashboard.
Replace fragmented tooling with a unified platform covering every attack surface — from DNS to OT/SCADA to cloud IAM. MITRE ATT&CK mapping, SHAP explainability, and sector-aware compliance scoring give you the evidence to act and the authority to report.
10× lower cost than SIEM · 94% detection accuracy
Procurement & Finance
📊
Predictable pricing. Measurable ROI. No surprise add-ons.
Flat subscription with no per-agent fees, no professional services onboarding, and no hidden compliance module costs. Compare SHIELD's all-inclusive pricing against your current SIEM + compliance + audit tooling stack — the numbers speak clearly.
Free → Enterprise plans · No lock-in · Cancel any time
SOC Analysts & IR Teams
🖥️
Less noise. Faster triage. Every alert explained.
SHAP explainability shows exactly which log factors drove each alert — no more guessing. Auto-created Jira/ServiceNow/Freshdesk tickets, outlier CSV export for forensics, voice-narrated summaries, and NLQ so you can ask your logs questions in plain English.
<2s analysis · ITSM auto-ticket · Zero false-positive guesswork
AI/ML & Technology Enthusiasts
🧠
Specialist ML solving real-world security at scale.
29 purpose-trained models — each domain-specific, independently versioned, and continuously improved. SHAP explainability on every prediction. Unsupervised anomaly detection catching zero-day patterns. NLQ interface bridging AI and human judgment. The Human-in-the-Loop architecture keeps analyst expertise central while AI handles the volume.
AI + Human · Explainable by design · Real-world deployment
SMEs → Large Enterprises
🏢
Enterprise-grade security. SME-friendly pricing.
Start free and scale without infrastructure changes. SMEs get enterprise-grade ML detection at a fraction of legacy SIEM cost. Large enterprises and corporates get the same platform with dedicated SLA, custom model retraining, and — for qualifying organisations — a fully air-gapped private deployment within your own environment.
Free tier → Private cloud deployment · Scale without rearchitecting
AI handles
Volume ingestion across 29 log types · Behavioural baseline learning · Anomaly scoring at machine speed · MITRE tactic tagging · Compliance gap computation · Draft ITSM tickets
⚖️
AI + Human
Balanced by design
Analysts decide
Threat context validation · Escalation judgement · False positive review · Remediation prioritisation · Board communication · Policy decisions
10×
Analyst throughput vs manual log review
<2s
From log upload to actionable intelligence
90%
Reduction in manual compliance prep time
$0
Agent installation · onboarding fees · hidden add-ons
Enterprise & Corporate · Private Deployment
SHIELD inside your perimeter — fully air-gapped.
For large enterprises and regulated corporates requiring data sovereignty, air-gapped deployment, or zero-cloud architecture — SHIELD is available as a fully private installation within your own infrastructure. Deployed under a formal agreement that includes usage governance, no reverse-engineering clauses, and dedicated Kenexoft engineering support for model updates and compliance framework additions.
✓ Air-gapped / on-premise deployment
✓ Custom model training on your data
✓ Data sovereignty guaranteed
✓ Dedicated engineering SLA
✓ Usage governance agreement
✓ Sector-specific compliance packs
Talk to Enterprise
Confidential brief · NDA available
Pricing

Less than your last security consultant invoice.

The average cost of a data breach is $4.45M. All plans include the full 29-model ML pipeline, ITSM integrations, and compliance monitoring.

Avg. Enterprise SIEM Cost
$22,000/mo
Plus professional services, agents, and onboarding
vs
You save up to $21,160/mo
SHIELD Enterprise
$840/mo
29 models · 12 compliance frameworks · Jira + ServiceNow + Freshdesk
Save ₹34,182/year
Essential
Choose any 5 log sources with 90-day retention
₹ 16,142
/month
Billed ₹193,698 every year
  • AI-Powered Insights
  • Custom Dashboards
  • API Access
  • Priority Support
  • Compliance Reports
  • White Labeling
  • SSO / SAML
  • Advanced Analytics
5 log types 30 GB 90-day retention
Get Started
Most Popular
Save ₹64,782/year
Professional
Choose any 10 log sources with 180-day retention
₹ 30,592
/month
Billed ₹367,098 every year
  • AI-Powered Insights
  • Custom Dashboards
  • API Access
  • Priority Support
  • Compliance Reports
  • White Labeling
  • SSO / SAML
  • Advanced Analytics
10 log types 90 GB 180-day retention
Get Started
Save ₹125,982/year
Enterprise
All log types with 240-day retention and full features
₹ 59,492
/month
Billed ₹713,898 every year
  • AI-Powered Insights
  • Custom Dashboards
  • API Access
  • Priority Support
  • Compliance Reports
  • White Labeling
  • SSO / SAML
  • Advanced Analytics
29 log types 200 GB 240-day retention
Get Started
All prices exclude applicable taxes
FAQ

Common questions answered.

Everything you need to know before uploading your first log file.

SHIELD v6.0 supports 29 log types: DNS, firewall, email/SMTP, endpoint/EDR, cloud (AWS/Azure/GCP), web server (Apache/Nginx/IIS), application, database (MySQL/MSSQL/PostgreSQL), identity/IAM/SSO/LDAP, user activity/UEBA, network/NetFlow, system/syslog, audit logs, vulnerability scans, threat intelligence feeds — plus 7 new types: OT/SCADA/ICS (Modbus, DNP3, OPC-UA), container/Kubernetes runtime, API gateway (Kong/APIGW/Nginx), cloud IAM (AWS CloudTrail/Azure AD/GCP IAM), DLP, NAC, and MFA events. Five compliance analyzers (GDPR, HIPAA, PCI-DSS, ISO 27001, SOC 2) are also included.
Yes — all three. SHIELD's SOAR playbook engine auto-creates tickets in Jira, ServiceNow, and Freshdesk when anomalies are detected. Tickets include full threat context: attack type, risk score (0–100), MITRE ATT&CK tactic, SHAP feature factors, affected asset, and recommended remediation steps. Status sync flows back from ITSM to SHIELD on resolution. Playbooks are configurable by severity, log type, and attack class — no code required.
No agents, no integrations, no configuration required for log analysis. Simply upload any log file in .csv, .log, .txt, .xls, or .xlsx format. SHIELD's dual-detection engine reads both filename and column content to automatically identify the log type and route it to the correct specialist ML model across all 29 types.
Each of SHIELD's 29 ML models is trained exclusively on its own log type — a DNS model sees only DNS telemetry, an OT/SCADA model only industrial protocol data. Proprietary multi-layer architecture runs supervised threat classification first, then unsupervised behavioural anomaly scoring — catching zero-day patterns no rule-based system can detect. Model architecture details are kept internal to protect the integrity of the detection engine.
SHIELD includes 12 compliance frameworks — activated based on your sector selection at registration. Universal: GDPR, HIPAA, PCI-DSS, SOC 2, ISO 27001, OWASP Top 10. Government: NIST CSF 2.0. Financial (EU): DORA. Healthcare extended: HITECH. Energy/OT: NERC CIP, IEC 62443. Life Sciences/Pharma: 21 CFR Part 11. All frameworks activate automatically — no extra modules or fees.
SHAP (SHapley Additive exPlanations) charts visually show which specific log features contributed most to a threat prediction and by how much. Every SHIELD prediction includes a SHAP chart — so your team can explain any alert to auditors, board members, or incident responders without black-box guesswork. For example, a Cloud IAM alert would show which account privilege factors, authentication posture gaps, and access pattern anomalies drove the risk score — in plain language your board and auditors can act on.
Your first threat analysis can run within 60 seconds of creating an account. Registration takes your sector and compliance obligations — SHIELD pre-configures the right frameworks and log type priorities immediately. No onboarding period, no agent installation, no infrastructure changes required.
Yes. The new OT/SCADA analyzer (v6.0) processes Modbus, DNP3, OPC-UA, and IEC 104 protocol logs alongside your existing IT log types. Cross-zone lateral movement from IT into OT segments is a key detection target — flagged when traffic from corporate/DMZ zones reaches ICS/PLC/SCADA zones. Compatible with Claroty, Nozomi, and Dragos log exports.
AI Cybersecurity Explained

Why AI-driven log analysis matters for every SOC.

Modern attacks evade signature-based tools. Here's how ML changes the equation — and why purpose-trained models outperform generic ones.

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The Limits of Rules-Based Detection

Traditional security systems rely on known attack signatures and manually-authored rules. They are effective only for threats that have been seen before. Modern adversaries — including automated botnets, credential-stuffing campaigns, OT-targeting APTs, and supply chain attacks — routinely bypass signature libraries through minor obfuscation. Rule-based systems require constant manual updates and still produce high false-positive rates that exhaust analyst capacity.

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How ML Models Detect Novel Threats

Machine learning models learn what normal behavior looks like across millions of log events — login velocity, DNS query entropy, OT function code risk, container namespace access patterns — and flag statistical deviations. This behavioral baseline approach means zero-day attacks, new malware families, and novel exfiltration techniques are detectable even without prior signatures. SHIELD's proprietary anomaly engine runs continuously across all 29 log types in parallel, catching what rule systems miss.

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Why Specialist Models Beat Generic Ones

A model trained across heterogeneous log types learns to compromise — it generalizes rather than specializes. SHIELD's architecture trains each model exclusively on its domain: a DNS model sees only DNS telemetry, an OT/SCADA model sees only industrial protocol data. Feature engineering is domain-specific (e.g., Modbus function code risk scoring for OT, push-count fatigue detection for MFA), attack class boundaries are sharper, and false-positive rates are dramatically lower. This is why SHIELD achieves 94% platform-wide accuracy where generic SIEM analytics average 70–75%.

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