Cisco vs Datadog

AI assistant for contact-centre agents and supervisors that produces call and transfer summaries, live transcription, suggested chat replies, topic analytics, automatic CSAT scoring and agent burnout signals.

AgenticOps workspace where teams and AI agents collaborate to investigate, correlate and resolve issues across domains: natural-language querying, multi-step agent workflows, shared real-time visibility, and native Cisco plus third-party tool integration via Cloud Control Studio.

End-to-end AI security product that discovers an organisation's AI assets, red-teams models and applications for vulnerabilities, and enforces runtime guardrails against prompt injection and data leakage.

Agentic support intelligence delivered inside Cisco Support and Professional Services — 'the delivery vehicle for everything Cisco Support and Professional Services knows about your environment, made continuously available before you ask for it' — generally available as SaaS since April 2026 and included with existing support contracts.

AI-native workforce engagement suite for contact centres that forecasts demand and optimises shifts, uses NLP and LLMs to evaluate 100 percent of human and AI agent interactions (AI Quality Management), and runs performance coaching and AI-led onboarding simulations.

Autonomous customer-service AI agent that handles inquiries conversationally across voice, SMS, email, chat and messaging apps and escalates to a human agent with context when it cannot resolve.

Detects AI-assisted pull requests from coding assistants such as Claude Code, Cursor and GitHub Copilot and compares them on adoption, PR throughput, cycle time, change failure rate and daily cost per active user.

Conversational AI interface for querying Datadog metrics, logs, traces and monitors in natural language and generating dashboards and notebooks, accessible from Datadog, Slack or mobile.

Datadog's Infrastructure-family product for shared GPU fleets across cloud, on-prem and neocloud providers: it links device health, cost and performance to the workloads and teams using them, alerts on unmet GPU requests, thermal throttling and ECC/XID errors, forecasts GPU demand and recommends optimisations such as reclaiming GPUs held by zombie processes. The page markets alerting, forecasting and recommendations but does not name a model or AI mechanism behind them.

Datadog's built-in AI engine: it continuously analyses metrics, traces and logs across the platform to raise anomaly alerts without configuration, detect faulty deployments by comparing code versions, run automated root-cause analysis on critical failures and surface tag-based insights and impact analysis. Available inside Infrastructure Monitoring, APM, Log Management and RUM rather than sold on its own.

Coding agent that triages production errors, regressions and vulnerabilities from Datadog telemetry, generates fixes with unit tests grounded in logs, traces and runtime variables, and opens pull requests for review.

AI SRE agent that autonomously investigates every alert the moment it fires, explores multiple root-cause hypotheses in parallel and reports findings into Slack, Jira, ServiceNow or GitHub.

Always-on AI SOC analyst that autonomously triages and investigates security alerts and delivers written investigation results to Datadog, Slack or Jira within minutes.