Enterprise Data AI — Semantic Layer

AI Agent — Managed Services

The 40 minutes your team loses at every incident. Eliminated.

Argus is built and running in production. Before your on-call engineer picks up the phone, it has already read the alerts, traced the changes, mapped the blast radius, and drafted the briefing.

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    • Built for
    • NOC teams
    • On-call engineers
    • Operations leads
    argus · investigation briefing
    LIVE INCIDENT · Provisioning Flow
    ▲ WHAT HAPPENED
    500 errors started at 01:58 UTC. Pattern isolated to Provisioning Flow. Error rate: 94% of requests.
    ↗ WHAT CHANGED
    Deployment at 23:41 UTC — commit: "update order timeout thresholds". No other deployments in window.
    ◎ BLAST RADIUS
    Feeds Order Manager and Symphonica. Customer Portal indirectly affected. No similar failures in past 30 days.
    ⚡ SUGGESTED ACTION
    Hypothesis: timeout misconfiguration from deployment. Roll back or increase downstream timeout to restore service.
    45→5min
    First hypothesis compressed from manual investigation to a ready-to-act briefing
    90s
    To map impact, correlate changes, and surface a structured incident summary
    40–70%
    Reduction in diagnosis time across NOC escalation, on-call, and shift handover
    This is the actual product

    Not a concept. Not a pilot.
    A working agent you can see today.

    Most vendors in this space are still building. Argus is running in production. Below is what your team would actually see — real screens, real output, real investigations.

    argus · investigation · Provisioning Flow
    Investigations
    P1
    Provisioning Flow
    01:58 UTC · 7m ago
    P2
    Billing timeout spike
    yesterday · 23:41
    P3
    Auth latency — EU-West
    2d ago · resolved
    P2
    Order Manager 500s
    4d ago · resolved
    P3
    DB conn pool — prod
    6d ago · resolved
    !
    HTTP 500 rate — Provisioning Flow · 43% of requests
    First alert: 01:58:14 UTC · Source: Datadog · env: prod-eu · pod: prov-flow-7d8f2
    What changed
    Deployment — prov-service v2.14.1 → v2.14.3 (feat: timeout config refactor)
    23:41 UTC
    Config change — EXTERNAL_API_TIMEOUT_MS set to 800ms (was 3000ms)
    23:39 UTC
    Blast radius
    prov-flow ✕ order-manager ✕ symphonica ✕ billing-svc ⚠ notif-service ⚠ auth-service ✓ reporting ✓
    3 services down · 2 at risk · customer-facing: YES — checkout affected
    Root cause hypothesis
    Argus · confidence 91%
    Timeout misconfiguration in v2.14.3 deploy. EXTERNAL_API_TIMEOUT_MS reduced from 3000ms to 800ms, below the p99 latency of upstream Identity Provider (avg 1,240ms). All 500s co-locate with identity validation calls. No similar failures in 45-day history.
    Suggested actions
    1
    Rollback prov-service to v2.14.1 or hot-patch timeout to ≥ 3000ms
    Now
    2
    Verify order-manager and symphonica error rates clear within 2 min of rollback
    Verify
    3
    Open post-mortem — config change bypassed staging timeout validation
    Follow-up
    Timeline
    23:39
    Config change pushed: EXTERNAL_API_TIMEOUT_MS → 800ms
    23:41
    v2.14.3 deployed to prod-eu · zero immediate errors
    01:51
    Identity Provider p99 begins drifting above 900ms (normal nightly pattern)
    01:58
    500 rate crosses 5% threshold · Datadog alert fires · Argus investigation starts
    02:00
    43% of provisioning requests failing · order-manager and symphonica cascade
    Investigation complete · 91s
    Sources: Datadog · GitHub · Elastic · Topology map
    1
    The complete incident briefing — what happened, what changed, blast radius, suggested action. One screen.
    argus · natural language query interface
    "What errors has Billing had in the last 2 hours?"
    Datadog: billing-svc logs Elastic: error traces Jaeger: span failures Topology: dependencies
    Argus · billing-svc · last 2h · prod-eu 02:07 UTC · 4 sources
    1,847
    Total errors
    43%
    Error rate
    1,240ms
    Avg latency
    00:14
    Since first error
    Error type Count Volume Sev First seen
    TIMEOUT identity-provider 1,204
    		High 01:58:14
    HTTP 504 payment-gateway 391
    		Med 01:59:02
    DB connection pool exhausted 189
    		Med 02:01:44
    NullPointerException line 412 63
    		Low 02:04:18
    Pattern detected: 65% of errors are identity-provider timeouts. Correlated with prov-service v2.14.3 deploy at 23:41 — EXTERNAL_API_TIMEOUT_MS now 800ms, below IdP p99 of 1,240ms. Billing errors are downstream of the Provisioning Flow incident.
    Sources Datadog Elastic Jaeger Topology map
    Ask: Which customers are affected? Show error rate over time What changed before this?
    billing-svc prod-eu
    Ask Argus anything about your stack...
    2
    Plain language in. Structured cross-tool answer out. No dashboard switching required.

    Works with your existing stack

    Datadog, Grafana, Elastic, Jaeger, GitHub, Jenkins, ServiceNow. Connects to the tools you already run. No rip-and-replace required.

    Ask in plain language, get structured answers

    “What errors has Billing had in the last 2 hours?” Argus calls the right tool, synthesises results, and surfaces the pattern. No dashboard hopping.

    Every investigation is stored and searchable

    Root cause, timeline, resolution path, affected services — all structured. Shift handover goes from a 30-minute verbal to a 5-minute review.

    Built for regulated environments

    Self-hosted deployment option. No incident data leaves your infrastructure. Designed for energy, telecom, and financial services operations.

    Want to see it on your incidents? Bring one real investigation. We'll run it live.
    How Argus works

    One agent. Every tool. One clear answer.

    Argus sits on top of your existing stack — no rip-and-replace. It reads from your monitoring, deployment, logging, and topology tools simultaneously, correlates the signals, and delivers a single structured briefing your team can act on immediately.

    YOUR STACK OUTPUT Monitoring Datadog · Grafana Elastic · Prometheus Deployments GitHub · Jenkins GitLab · ArgoCD Logging & Traces Elastic · Jaeger Splunk · Loki Service Topology Service catalog Dependency maps Incident History Past investigations Root causes · Patterns Argus AI INVESTIGATION AGENT Signal correlation Change linking Blast-radius map ▲ WHAT HAPPENED Root cause & error pattern Timeline · Severity scope ↗ WHAT CHANGED Deployments · Commits Config changes correlated ◎ BLAST RADIUS Affected services mapped Customer-facing impact ⚡ SUGGESTED ACTION Hypothesis + first step Ready to act in 90 seconds Before the phone rings 90 seconds
    Built for real operations

    Four scenarios where Argus changes the outcome.

    Ask in plain language. Get cross-tool answers. Act with confidence.

    01

    NOC escalation decisions

    Know immediately if an alert is a blip or a P0 incident.

    02

    Cross-tool error investigation

    One question instead of five dashboards.

    03

    The 2 AM on-call briefing

    Direction in 90 seconds instead of 45 minutes.

    04

    Shift handover catch-up

    Full overnight context in 5 minutes, not 30.

    Measurable results

    The MTTR impact, by scenario.

    Scenario Today With Argus
    Time to first hypothesis 20–45 min ~2 min
    NOC escalation decision Gut feel or wait Topology + impact in 90s
    Deployment correlation Manual GitHub / Jenkins Automatic, every investigation
    Recurring issue recognition "I think this happened before..." Structured history with root cause
    Shift handover catch-up 20–30 min 5 min investigation log review
    Cross-service impact Multi-tool navigation Blast radius on topology, instant
    Ready when you are

    See what Argus could do for your operations team

    We start by mapping your incident workflow, service topolgy, and monitoring stack. Then we shos you exactly where Argus cuts diagnosis time and improves escalation accuracy. No commitment requred. 

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