AI + Security

AI Cybersecurity Solutions for Modern Enterprises

Iedeo builds AI-powered cybersecurity — anomaly detection at scale, intelligent threat response, secure LLM deployment, and defenses against prompt injection, data exfiltration, and model abuse.

<1s
Detection Latency
99.7%
Anomaly Precision
10x
SOC Throughput
24/7
Continuous

Security teams are drowning, attackers are using AI

🚨

Alert fatigue

SOC analysts triage 1000s of alerts/day — most are noise. Critical signal gets buried.

🤖

AI-powered attackers

Phishing, deepfakes, and automated reconnaissance are now LLM-driven. Defense must match.

💉

LLM prompt injection

Enterprise GenAI apps are vulnerable to prompt injection, data exfiltration, jailbreaks.

👤

Insider risk

Behavioural anomalies in user activity often go undetected by rule-based SIEMs.

📂

Sensitive data in LLMs

Employees paste customer data into ChatGPT every day — no visibility, no controls.

🔓

Shadow AI

Unsanctioned AI tools enter your stack — security teams find out months later.

Iedeo AI security capabilities

🔍

AI-driven anomaly detection

Unsupervised models detect deviations in network, application and user behaviour at scale.

  • Streaming pipelines on logs
  • Behavioural baselines per user
  • Explainable scoring
🛡️

LLM security testing

Red-team your production LLM apps — prompt injection, data exfil, jailbreak, output integrity.

  • Automated adversarial probes
  • Manual expert pentest
  • Findings + fixes report
🚪

GenAI guardrails

Input/output filtering for production LLM applications — PII redaction, toxicity, secret leakage.

  • Real-time content filters
  • Per-tenant policies
  • Audit-friendly logging
🎯

Threat intelligence AI

LLM-powered analyst copilot — summarise alerts, link IOCs, suggest playbook actions.

  • SIEM/SOAR integration
  • Natural-language queries
  • Auto-enriched alerts
👁️

AI usage monitoring

See which employees are pasting what into which LLM tools. Block sensitive data leakage.

  • Browser + endpoint visibility
  • Auto-redaction at proxy
  • Per-team policy enforcement
🧪

Secure AI deployment

Architecture review and hardening for in-house LLM, RAG and agent applications.

  • Threat modelling per app
  • OWASP-LLM Top 10 alignment
  • On-prem & VPC patterns

Our Delivery Process

01

Current-state assessment

Inventory your AI applications, LLM use, security posture and data exposure. Output: prioritised risk map.

02

Threat modelling

For each AI application, model adversaries, attack surfaces, and data-loss scenarios. Map to OWASP-LLM Top 10.

03

Build defenses

Implement guardrails, anomaly detection, monitoring, and red-team test harnesses. Integrate with your SIEM/SOAR.

04

Red-team exercise

Live adversarial testing of your LLM apps and AI infrastructure by our offensive security team.

05

Continuous improvement

Monthly retainer for new attack vectors, model updates, and policy tuning. Quarterly red-team refreshes.

Industries We Serve

🏦

Banking & FinTech

Transaction anomaly, fraud detection, regulator-aligned AI governance.

🛡️

Insurance

Claim fraud detection, AI-enabled underwriting controls.

🏥

Healthcare

Patient data DLP, HIPAA-aligned LLM deployment, medical-image AI security.

🛒

E-commerce

Bot defense, fraud detection, AI-driven checkout security.

🏢

Enterprise SaaS

Secure copilot deployment, customer-data isolation, RAG safety.

🏛️

Government

OSINT analysis, deepfake detection, regional-language threat intel.

🚀

AI-first startups

Pre-launch LLM penetration testing, secure-by-design architecture.

⚖️

Legal

Confidential document handling, AI tool governance, audit trails.

Why pick Iedeo for AI security

AI + security, not bolted together

We are an AI company that learned security — not a security shop that bought AI. We understand attack vectors deeply.

Hands-on red team

We have broken (responsibly) into production LLM apps for clients in BFSI, healthcare and SaaS. We know what real attackers do.

OWASP-LLM Top 10 expertise

Prompt injection, insecure output handling, training data poisoning, model DoS — we have built defenses for all 10.

India-data-residency capable

Full on-prem and VPC deployment, no foreign API dependencies for sensitive workloads.

Honest scope

No FUD-driven selling. We tell you which risks are realistic, which are theoretical, and where to invest first.

CERT-In / SEBI aware

We design for Indian regulatory expectations — incident reporting timelines, audit trails, AI governance.

Frequently Asked Questions

Common questions about our services and technology.

What is AI cybersecurity?

Two things: (1) using AI to defend your enterprise (anomaly detection, alert triage, threat intelligence) and (2) securing the AI applications you build (prompt injection, LLM red-teaming, GenAI guardrails). Iedeo does both.

Can you red-team our production LLM application?

Yes. We run prompt-injection, jailbreak, data-exfiltration, output-integrity and denial-of-service tests against your live or staging LLM application — with your authorisation. We deliver a CVE-style findings report with proof of concept and remediation.

How do you handle data residency for Indian regulators?

For BFSI, healthcare and government workloads, we deploy fully in your VPC or on-prem with no external API calls. Self-hosted LLMs (Llama 3, Mistral) replace external providers when required.

What does an AI security project cost?

LLM red-team: ₹4-12L per application. Full AI security architecture review + guardrails build: ₹15-40L. Ongoing retainer: ₹2-6L/month. Pricing depends on scope, frequency, and number of applications.

Do you integrate with our SIEM/SOAR?

Yes. We integrate with Splunk, Microsoft Sentinel, Chronicle, Elastic Security, IBM QRadar, and most SOAR platforms. AI-enriched alerts flow into your existing analyst workflow.

How does AI anomaly detection differ from rule-based SIEM?

Rules detect known patterns. AI detects deviations from learned normal behaviour — catches novel attacks, insider risks, and zero-days that rules miss. Most enterprises run both in parallel.

Do you offer one-off pentests or only retainers?

Both. Single-engagement LLM red-team is common. Retainers make sense for organisations with multiple LLM apps shipping continuously.

Get a free 1-hour AI security risk briefing

We will walk you through the top 5 AI-specific risks for your organisation, what attacks look like in practice, and what good defense looks like — tailored to your stack.