IBM vs Zscaler

Protects enterprise data across AI agents, applications and endpoints against agentic-AI, regulatory and post-quantum risks.

Full-stack application and infrastructure observability powered by agentic AI, including automatic discovery/mapping of GenAI workflows and AI-driven Smart Alerts to reduce alert fatigue.

AI-driven robotic process automation for building intelligent bots that automate business processes, with AI-embedded resilience built into the RPA runtime.

Visual data-science and machine-learning platform for building predictive models, with advanced algorithms, model deployment and open-source framework integration.

Document intelligence platform using OCR, NLP enrichments (entity/sentiment/emotion/category extraction) and LLM integration to automate information discovery from enterprise documents.

Deep-learning text analytics service extracting entities, sentiment, emotion, concepts, semantic roles and custom classifications from unstructured text.

A speech recognition API that converts audio into real-time or batch text for transcription, captioning and voice-analytics use cases.

A text-to-speech API that converts text into multilingual synthesized speech using neural voices.

An AI coding agent that automates planning, code generation, review and verification across the software development lifecycle, including IBM Z mainframe modernization workflows.

A generative AI assistant for IBM Z mainframe application discovery, code generation, refactoring and modernization.

An agentic AI IT-operations platform that unifies observability, optimization and automated remediation across applications, infrastructure and networks.

Studio for building, tuning and deploying model-based applications on IBM and third-party foundation models.

A governance platform providing real-time visibility, policy enforcement and accountability tracking for AI models and agents across the AI lifecycle.

Governance layer for employee use of generative AI that discovers shadow AI applications, applies allow, block or coach policies per user, and monitors prompts and responses against more than 100 data loss prevention dictionaries to stop sensitive data leaving through AI tools.

AI security posture management that auto-discovers and classifies AI models, agents and services across Azure AI Foundry, Amazon Bedrock, Google Vertex AI and unmanaged providers, correlates the sensitive data connected to them, and maps findings to frameworks including NIST AI RMF 600-1 and the EU AI Act.

Runs AI models over the security data flowing through the Zero Trust Exchange, using attack graphs, user risk scoring and threat intelligence to score the probability of a breach, forecast an attacker's next tactics, and recommend policy changes before the attack completes.

AI-driven detection and diagnosis of digital-experience issues across the network and application delivery path.

Real-time guardrails for LLM traffic that inspect prompts and responses inline to block prompt injection, jailbreaks, sensitive-data leakage and toxic or off-topic output, deployed either as a proxy or as an API-based Detection as a Service.

Inline, AI-powered sandbox that analyzes unknown files in real time to block zero-day and file-based malware before it reaches endpoints, using AI/ML models trained on 600M+ samples.

Automated adversarial testing for AI applications and agents that runs simulated attacks using 25+ predefined and custom probes across text, image, voice and document inputs, scoring results for security, safety, hallucination and business alignment against MITRE ATLAS, NIST AI RMF and the OWASP LLM Top 10.

Cloud-native security platform that inspects and enforces policy on every connection between users, devices, workloads and AI agents, rather than trusting anything on a corporate network.